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.claude-plugin/plugin.json Normal file
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{
"name": "superpowers",
"description": "Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques",
"version": "3.5.1",
"author": {
"name": "Jesse Vincent",
"email": "jesse@fsck.com"
},
"skills": [
"./skills"
],
"agents": [
"./agents"
],
"commands": [
"./commands"
],
"hooks": [
"./hooks"
]
}

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README.md Normal file
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# superpowers
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques

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agents/code-reviewer.md Normal file
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---
name: code-reviewer
description: |
Use this agent when a major project step has been completed and needs to be reviewed against the original plan and coding standards. Examples: <example>Context: The user is creating a code-review agent that should be called after a logical chunk of code is written. user: "I've finished implementing the user authentication system as outlined in step 3 of our plan" assistant: "Great work! Now let me use the code-reviewer agent to review the implementation against our plan and coding standards" <commentary>Since a major project step has been completed, use the code-reviewer agent to validate the work against the plan and identify any issues.</commentary></example> <example>Context: User has completed a significant feature implementation. user: "The API endpoints for the task management system are now complete - that covers step 2 from our architecture document" assistant: "Excellent! Let me have the code-reviewer agent examine this implementation to ensure it aligns with our plan and follows best practices" <commentary>A numbered step from the planning document has been completed, so the code-reviewer agent should review the work.</commentary></example>
model: sonnet
---
You are a Senior Code Reviewer with expertise in software architecture, design patterns, and best practices. Your role is to review completed project steps against original plans and ensure code quality standards are met.
When reviewing completed work, you will:
1. **Plan Alignment Analysis**:
- Compare the implementation against the original planning document or step description
- Identify any deviations from the planned approach, architecture, or requirements
- Assess whether deviations are justified improvements or problematic departures
- Verify that all planned functionality has been implemented
2. **Code Quality Assessment**:
- Review code for adherence to established patterns and conventions
- Check for proper error handling, type safety, and defensive programming
- Evaluate code organization, naming conventions, and maintainability
- Assess test coverage and quality of test implementations
- Look for potential security vulnerabilities or performance issues
3. **Architecture and Design Review**:
- Ensure the implementation follows SOLID principles and established architectural patterns
- Check for proper separation of concerns and loose coupling
- Verify that the code integrates well with existing systems
- Assess scalability and extensibility considerations
4. **Documentation and Standards**:
- Verify that code includes appropriate comments and documentation
- Check that file headers, function documentation, and inline comments are present and accurate
- Ensure adherence to project-specific coding standards and conventions
5. **Issue Identification and Recommendations**:
- Clearly categorize issues as: Critical (must fix), Important (should fix), or Suggestions (nice to have)
- For each issue, provide specific examples and actionable recommendations
- When you identify plan deviations, explain whether they're problematic or beneficial
- Suggest specific improvements with code examples when helpful
6. **Communication Protocol**:
- If you find significant deviations from the plan, ask the coding agent to review and confirm the changes
- If you identify issues with the original plan itself, recommend plan updates
- For implementation problems, provide clear guidance on fixes needed
- Always acknowledge what was done well before highlighting issues
Your output should be structured, actionable, and focused on helping maintain high code quality while ensuring project goals are met. Be thorough but concise, and always provide constructive feedback that helps improve both the current implementation and future development practices.

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commands/brainstorm.md Normal file
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---
description: Interactive design refinement using Socratic method
---
Use and follow the brainstorming skill exactly as written

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commands/execute-plan.md Normal file
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---
description: Execute plan in batches with review checkpoints
---
Use the executing-plans skill exactly as written

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commands/write-plan.md Normal file
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---
description: Create detailed implementation plan with bite-sized tasks
---
Use the writing-plans skill exactly as written

15
hooks/hooks.json Normal file
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{
"hooks": {
"SessionStart": [
{
"matcher": "startup|resume|clear|compact",
"hooks": [
{
"type": "command",
"command": "${CLAUDE_PLUGIN_ROOT}/hooks/session-start.sh"
}
]
}
]
}
}

34
hooks/session-start.sh Executable file
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#!/usr/bin/env bash
# SessionStart hook for superpowers plugin
set -euo pipefail
# Determine plugin root directory
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]:-$0}")" && pwd)"
PLUGIN_ROOT="$(cd "${SCRIPT_DIR}/.." && pwd)"
# Check if legacy skills directory exists and build warning
warning_message=""
legacy_skills_dir="${HOME}/.config/superpowers/skills"
if [ -d "$legacy_skills_dir" ]; then
warning_message="\n\n<important-reminder>IN YOUR FIRST REPLY AFTER SEEING THIS MESSAGE YOU MUST TELL THE USER:⚠️ **WARNING:** Superpowers now uses Claude Code's skills system. Custom skills in ~/.config/superpowers/skills will not be read. Move custom skills to ~/.claude/skills instead. To make this message go away, remove ~/.config/superpowers/skills</important-reminder>"
fi
# Read using-superpowers content
using_superpowers_content=$(cat "${PLUGIN_ROOT}/skills/using-superpowers/SKILL.md" 2>&1 || echo "Error reading using-superpowers skill")
# Escape outputs for JSON
using_superpowers_escaped=$(echo "$using_superpowers_content" | sed 's/\\/\\\\/g' | sed 's/"/\\"/g' | awk '{printf "%s\\n", $0}')
warning_escaped=$(echo "$warning_message" | sed 's/\\/\\\\/g' | sed 's/"/\\"/g' | awk '{printf "%s\\n", $0}')
# Output context injection as JSON
cat <<EOF
{
"hookSpecificOutput": {
"hookEventName": "SessionStart",
"additionalContext": "<EXTREMELY_IMPORTANT>\nYou have superpowers.\n\n**Below is the full content of your 'superpowers:using-superpowers' skill - your introduction to using skills. For all other skills, use the 'Skill' tool:**\n\n${using_superpowers_escaped}\n\n${warning_escaped}\n</EXTREMELY_IMPORTANT>"
}
}
EOF
exit 0

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plugin.lock.json Normal file
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{
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"name": "superpowers",
"description": "Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques",
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---
name: brainstorming
description: Use when creating or developing, before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning, alternative exploration, and incremental validation. Don't use during clear 'mechanical' processes
---
# Brainstorming Ideas Into Designs
## Overview
Help turn ideas into fully formed designs and specs through natural collaborative dialogue.
Start by understanding the current project context, then ask questions one at a time to refine the idea. Once you understand what you're building, present the design in small sections (200-300 words), checking after each section whether it looks right so far.
## The Process
**Understanding the idea:**
- Check out the current project state first (files, docs, recent commits)
- Ask questions one at a time to refine the idea
- Prefer multiple choice questions when possible, but open-ended is fine too
- Only one question per message - if a topic needs more exploration, break it into multiple questions
- Focus on understanding: purpose, constraints, success criteria
**Exploring approaches:**
- Propose 2-3 different approaches with trade-offs
- Present options conversationally with your recommendation and reasoning
- Lead with your recommended option and explain why
**Presenting the design:**
- Once you believe you understand what you're building, present the design
- Break it into sections of 200-300 words
- Ask after each section whether it looks right so far
- Cover: architecture, components, data flow, error handling, testing
- Be ready to go back and clarify if something doesn't make sense
## After the Design
**Documentation:**
- Write the validated design to `docs/plans/YYYY-MM-DD-<topic>-design.md`
- Use elements-of-style:writing-clearly-and-concisely skill if available
- Commit the design document to git
**Implementation (if continuing):**
- Ask: "Ready to set up for implementation?"
- Use superpowers:using-git-worktrees to create isolated workspace
- Use superpowers:writing-plans to create detailed implementation plan
## Key Principles
- **One question at a time** - Don't overwhelm with multiple questions
- **Multiple choice preferred** - Easier to answer than open-ended when possible
- **YAGNI ruthlessly** - Remove unnecessary features from all designs
- **Explore alternatives** - Always propose 2-3 approaches before settling
- **Incremental validation** - Present design in sections, validate each
- **Be flexible** - Go back and clarify when something doesn't make sense

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---
name: condition-based-waiting
description: Use when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guesses
---
# Condition-Based Waiting
## Overview
Flaky tests often guess at timing with arbitrary delays. This creates race conditions where tests pass on fast machines but fail under load or in CI.
**Core principle:** Wait for the actual condition you care about, not a guess about how long it takes.
## When to Use
```dot
digraph when_to_use {
"Test uses setTimeout/sleep?" [shape=diamond];
"Testing timing behavior?" [shape=diamond];
"Document WHY timeout needed" [shape=box];
"Use condition-based waiting" [shape=box];
"Test uses setTimeout/sleep?" -> "Testing timing behavior?" [label="yes"];
"Testing timing behavior?" -> "Document WHY timeout needed" [label="yes"];
"Testing timing behavior?" -> "Use condition-based waiting" [label="no"];
}
```
**Use when:**
- Tests have arbitrary delays (`setTimeout`, `sleep`, `time.sleep()`)
- Tests are flaky (pass sometimes, fail under load)
- Tests timeout when run in parallel
- Waiting for async operations to complete
**Don't use when:**
- Testing actual timing behavior (debounce, throttle intervals)
- Always document WHY if using arbitrary timeout
## Core Pattern
```typescript
// ❌ BEFORE: Guessing at timing
await new Promise(r => setTimeout(r, 50));
const result = getResult();
expect(result).toBeDefined();
// ✅ AFTER: Waiting for condition
await waitFor(() => getResult() !== undefined);
const result = getResult();
expect(result).toBeDefined();
```
## Quick Patterns
| Scenario | Pattern |
|----------|---------|
| Wait for event | `waitFor(() => events.find(e => e.type === 'DONE'))` |
| Wait for state | `waitFor(() => machine.state === 'ready')` |
| Wait for count | `waitFor(() => items.length >= 5)` |
| Wait for file | `waitFor(() => fs.existsSync(path))` |
| Complex condition | `waitFor(() => obj.ready && obj.value > 10)` |
## Implementation
Generic polling function:
```typescript
async function waitFor<T>(
condition: () => T | undefined | null | false,
description: string,
timeoutMs = 5000
): Promise<T> {
const startTime = Date.now();
while (true) {
const result = condition();
if (result) return result;
if (Date.now() - startTime > timeoutMs) {
throw new Error(`Timeout waiting for ${description} after ${timeoutMs}ms`);
}
await new Promise(r => setTimeout(r, 10)); // Poll every 10ms
}
}
```
See @example.ts for complete implementation with domain-specific helpers (`waitForEvent`, `waitForEventCount`, `waitForEventMatch`) from actual debugging session.
## Common Mistakes
**❌ Polling too fast:** `setTimeout(check, 1)` - wastes CPU
**✅ Fix:** Poll every 10ms
**❌ No timeout:** Loop forever if condition never met
**✅ Fix:** Always include timeout with clear error
**❌ Stale data:** Cache state before loop
**✅ Fix:** Call getter inside loop for fresh data
## When Arbitrary Timeout IS Correct
```typescript
// Tool ticks every 100ms - need 2 ticks to verify partial output
await waitForEvent(manager, 'TOOL_STARTED'); // First: wait for condition
await new Promise(r => setTimeout(r, 200)); // Then: wait for timed behavior
// 200ms = 2 ticks at 100ms intervals - documented and justified
```
**Requirements:**
1. First wait for triggering condition
2. Based on known timing (not guessing)
3. Comment explaining WHY
## Real-World Impact
From debugging session (2025-10-03):
- Fixed 15 flaky tests across 3 files
- Pass rate: 60% → 100%
- Execution time: 40% faster
- No more race conditions

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// Complete implementation of condition-based waiting utilities
// From: Lace test infrastructure improvements (2025-10-03)
// Context: Fixed 15 flaky tests by replacing arbitrary timeouts
import type { ThreadManager } from '~/threads/thread-manager';
import type { LaceEvent, LaceEventType } from '~/threads/types';
/**
* Wait for a specific event type to appear in thread
*
* @param threadManager - The thread manager to query
* @param threadId - Thread to check for events
* @param eventType - Type of event to wait for
* @param timeoutMs - Maximum time to wait (default 5000ms)
* @returns Promise resolving to the first matching event
*
* Example:
* await waitForEvent(threadManager, agentThreadId, 'TOOL_RESULT');
*/
export function waitForEvent(
threadManager: ThreadManager,
threadId: string,
eventType: LaceEventType,
timeoutMs = 5000
): Promise<LaceEvent> {
return new Promise((resolve, reject) => {
const startTime = Date.now();
const check = () => {
const events = threadManager.getEvents(threadId);
const event = events.find((e) => e.type === eventType);
if (event) {
resolve(event);
} else if (Date.now() - startTime > timeoutMs) {
reject(new Error(`Timeout waiting for ${eventType} event after ${timeoutMs}ms`));
} else {
setTimeout(check, 10); // Poll every 10ms for efficiency
}
};
check();
});
}
/**
* Wait for a specific number of events of a given type
*
* @param threadManager - The thread manager to query
* @param threadId - Thread to check for events
* @param eventType - Type of event to wait for
* @param count - Number of events to wait for
* @param timeoutMs - Maximum time to wait (default 5000ms)
* @returns Promise resolving to all matching events once count is reached
*
* Example:
* // Wait for 2 AGENT_MESSAGE events (initial response + continuation)
* await waitForEventCount(threadManager, agentThreadId, 'AGENT_MESSAGE', 2);
*/
export function waitForEventCount(
threadManager: ThreadManager,
threadId: string,
eventType: LaceEventType,
count: number,
timeoutMs = 5000
): Promise<LaceEvent[]> {
return new Promise((resolve, reject) => {
const startTime = Date.now();
const check = () => {
const events = threadManager.getEvents(threadId);
const matchingEvents = events.filter((e) => e.type === eventType);
if (matchingEvents.length >= count) {
resolve(matchingEvents);
} else if (Date.now() - startTime > timeoutMs) {
reject(
new Error(
`Timeout waiting for ${count} ${eventType} events after ${timeoutMs}ms (got ${matchingEvents.length})`
)
);
} else {
setTimeout(check, 10);
}
};
check();
});
}
/**
* Wait for an event matching a custom predicate
* Useful when you need to check event data, not just type
*
* @param threadManager - The thread manager to query
* @param threadId - Thread to check for events
* @param predicate - Function that returns true when event matches
* @param description - Human-readable description for error messages
* @param timeoutMs - Maximum time to wait (default 5000ms)
* @returns Promise resolving to the first matching event
*
* Example:
* // Wait for TOOL_RESULT with specific ID
* await waitForEventMatch(
* threadManager,
* agentThreadId,
* (e) => e.type === 'TOOL_RESULT' && e.data.id === 'call_123',
* 'TOOL_RESULT with id=call_123'
* );
*/
export function waitForEventMatch(
threadManager: ThreadManager,
threadId: string,
predicate: (event: LaceEvent) => boolean,
description: string,
timeoutMs = 5000
): Promise<LaceEvent> {
return new Promise((resolve, reject) => {
const startTime = Date.now();
const check = () => {
const events = threadManager.getEvents(threadId);
const event = events.find(predicate);
if (event) {
resolve(event);
} else if (Date.now() - startTime > timeoutMs) {
reject(new Error(`Timeout waiting for ${description} after ${timeoutMs}ms`));
} else {
setTimeout(check, 10);
}
};
check();
});
}
// Usage example from actual debugging session:
//
// BEFORE (flaky):
// ---------------
// const messagePromise = agent.sendMessage('Execute tools');
// await new Promise(r => setTimeout(r, 300)); // Hope tools start in 300ms
// agent.abort();
// await messagePromise;
// await new Promise(r => setTimeout(r, 50)); // Hope results arrive in 50ms
// expect(toolResults.length).toBe(2); // Fails randomly
//
// AFTER (reliable):
// ----------------
// const messagePromise = agent.sendMessage('Execute tools');
// await waitForEventCount(threadManager, threadId, 'TOOL_CALL', 2); // Wait for tools to start
// agent.abort();
// await messagePromise;
// await waitForEventCount(threadManager, threadId, 'TOOL_RESULT', 2); // Wait for results
// expect(toolResults.length).toBe(2); // Always succeeds
//
// Result: 60% pass rate → 100%, 40% faster execution

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---
name: defense-in-depth
description: Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
---
# Defense-in-Depth Validation
## Overview
When you fix a bug caused by invalid data, adding validation at one place feels sufficient. But that single check can be bypassed by different code paths, refactoring, or mocks.
**Core principle:** Validate at EVERY layer data passes through. Make the bug structurally impossible.
## Why Multiple Layers
Single validation: "We fixed the bug"
Multiple layers: "We made the bug impossible"
Different layers catch different cases:
- Entry validation catches most bugs
- Business logic catches edge cases
- Environment guards prevent context-specific dangers
- Debug logging helps when other layers fail
## The Four Layers
### Layer 1: Entry Point Validation
**Purpose:** Reject obviously invalid input at API boundary
```typescript
function createProject(name: string, workingDirectory: string) {
if (!workingDirectory || workingDirectory.trim() === '') {
throw new Error('workingDirectory cannot be empty');
}
if (!existsSync(workingDirectory)) {
throw new Error(`workingDirectory does not exist: ${workingDirectory}`);
}
if (!statSync(workingDirectory).isDirectory()) {
throw new Error(`workingDirectory is not a directory: ${workingDirectory}`);
}
// ... proceed
}
```
### Layer 2: Business Logic Validation
**Purpose:** Ensure data makes sense for this operation
```typescript
function initializeWorkspace(projectDir: string, sessionId: string) {
if (!projectDir) {
throw new Error('projectDir required for workspace initialization');
}
// ... proceed
}
```
### Layer 3: Environment Guards
**Purpose:** Prevent dangerous operations in specific contexts
```typescript
async function gitInit(directory: string) {
// In tests, refuse git init outside temp directories
if (process.env.NODE_ENV === 'test') {
const normalized = normalize(resolve(directory));
const tmpDir = normalize(resolve(tmpdir()));
if (!normalized.startsWith(tmpDir)) {
throw new Error(
`Refusing git init outside temp dir during tests: ${directory}`
);
}
}
// ... proceed
}
```
### Layer 4: Debug Instrumentation
**Purpose:** Capture context for forensics
```typescript
async function gitInit(directory: string) {
const stack = new Error().stack;
logger.debug('About to git init', {
directory,
cwd: process.cwd(),
stack,
});
// ... proceed
}
```
## Applying the Pattern
When you find a bug:
1. **Trace the data flow** - Where does bad value originate? Where used?
2. **Map all checkpoints** - List every point data passes through
3. **Add validation at each layer** - Entry, business, environment, debug
4. **Test each layer** - Try to bypass layer 1, verify layer 2 catches it
## Example from Session
Bug: Empty `projectDir` caused `git init` in source code
**Data flow:**
1. Test setup → empty string
2. `Project.create(name, '')`
3. `WorkspaceManager.createWorkspace('')`
4. `git init` runs in `process.cwd()`
**Four layers added:**
- Layer 1: `Project.create()` validates not empty/exists/writable
- Layer 2: `WorkspaceManager` validates projectDir not empty
- Layer 3: `WorktreeManager` refuses git init outside tmpdir in tests
- Layer 4: Stack trace logging before git init
**Result:** All 1847 tests passed, bug impossible to reproduce
## Key Insight
All four layers were necessary. During testing, each layer caught bugs the others missed:
- Different code paths bypassed entry validation
- Mocks bypassed business logic checks
- Edge cases on different platforms needed environment guards
- Debug logging identified structural misuse
**Don't stop at one validation point.** Add checks at every layer.

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---
name: dispatching-parallel-agents
description: Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
---
# Dispatching Parallel Agents
## Overview
When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.
**Core principle:** Dispatch one agent per independent problem domain. Let them work concurrently.
## When to Use
```dot
digraph when_to_use {
"Multiple failures?" [shape=diamond];
"Are they independent?" [shape=diamond];
"Single agent investigates all" [shape=box];
"One agent per problem domain" [shape=box];
"Can they work in parallel?" [shape=diamond];
"Sequential agents" [shape=box];
"Parallel dispatch" [shape=box];
"Multiple failures?" -> "Are they independent?" [label="yes"];
"Are they independent?" -> "Single agent investigates all" [label="no - related"];
"Are they independent?" -> "Can they work in parallel?" [label="yes"];
"Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
"Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}
```
**Use when:**
- 3+ test files failing with different root causes
- Multiple subsystems broken independently
- Each problem can be understood without context from others
- No shared state between investigations
**Don't use when:**
- Failures are related (fix one might fix others)
- Need to understand full system state
- Agents would interfere with each other
## The Pattern
### 1. Identify Independent Domains
Group failures by what's broken:
- File A tests: Tool approval flow
- File B tests: Batch completion behavior
- File C tests: Abort functionality
Each domain is independent - fixing tool approval doesn't affect abort tests.
### 2. Create Focused Agent Tasks
Each agent gets:
- **Specific scope:** One test file or subsystem
- **Clear goal:** Make these tests pass
- **Constraints:** Don't change other code
- **Expected output:** Summary of what you found and fixed
### 3. Dispatch in Parallel
```typescript
// In Claude Code / AI environment
Task("Fix agent-tool-abort.test.ts failures")
Task("Fix batch-completion-behavior.test.ts failures")
Task("Fix tool-approval-race-conditions.test.ts failures")
// All three run concurrently
```
### 4. Review and Integrate
When agents return:
- Read each summary
- Verify fixes don't conflict
- Run full test suite
- Integrate all changes
## Agent Prompt Structure
Good agent prompts are:
1. **Focused** - One clear problem domain
2. **Self-contained** - All context needed to understand the problem
3. **Specific about output** - What should the agent return?
```markdown
Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:
1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed
3. "should properly track pendingToolCount" - expects 3 results but gets 0
These are timing/race condition issues. Your task:
1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
- Replacing arbitrary timeouts with event-based waiting
- Fixing bugs in abort implementation if found
- Adjusting test expectations if testing changed behavior
Do NOT just increase timeouts - find the real issue.
Return: Summary of what you found and what you fixed.
```
## Common Mistakes
**❌ Too broad:** "Fix all the tests" - agent gets lost
**✅ Specific:** "Fix agent-tool-abort.test.ts" - focused scope
**❌ No context:** "Fix the race condition" - agent doesn't know where
**✅ Context:** Paste the error messages and test names
**❌ No constraints:** Agent might refactor everything
**✅ Constraints:** "Do NOT change production code" or "Fix tests only"
**❌ Vague output:** "Fix it" - you don't know what changed
**✅ Specific:** "Return summary of root cause and changes"
## When NOT to Use
**Related failures:** Fixing one might fix others - investigate together first
**Need full context:** Understanding requires seeing entire system
**Exploratory debugging:** You don't know what's broken yet
**Shared state:** Agents would interfere (editing same files, using same resources)
## Real Example from Session
**Scenario:** 6 test failures across 3 files after major refactoring
**Failures:**
- agent-tool-abort.test.ts: 3 failures (timing issues)
- batch-completion-behavior.test.ts: 2 failures (tools not executing)
- tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)
**Decision:** Independent domains - abort logic separate from batch completion separate from race conditions
**Dispatch:**
```
Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts
```
**Results:**
- Agent 1: Replaced timeouts with event-based waiting
- Agent 2: Fixed event structure bug (threadId in wrong place)
- Agent 3: Added wait for async tool execution to complete
**Integration:** All fixes independent, no conflicts, full suite green
**Time saved:** 3 problems solved in parallel vs sequentially
## Key Benefits
1. **Parallelization** - Multiple investigations happen simultaneously
2. **Focus** - Each agent has narrow scope, less context to track
3. **Independence** - Agents don't interfere with each other
4. **Speed** - 3 problems solved in time of 1
## Verification
After agents return:
1. **Review each summary** - Understand what changed
2. **Check for conflicts** - Did agents edit same code?
3. **Run full suite** - Verify all fixes work together
4. **Spot check** - Agents can make systematic errors
## Real-World Impact
From debugging session (2025-10-03):
- 6 failures across 3 files
- 3 agents dispatched in parallel
- All investigations completed concurrently
- All fixes integrated successfully
- Zero conflicts between agent changes

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---
name: executing-plans
description: Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically, executes tasks in batches, reports for review between batches
---
# Executing Plans
## Overview
Load plan, review critically, execute tasks in batches, report for review between batches.
**Core principle:** Batch execution with checkpoints for architect review.
**Announce at start:** "I'm using the executing-plans skill to implement this plan."
## The Process
### Step 1: Load and Review Plan
1. Read plan file
2. Review critically - identify any questions or concerns about the plan
3. If concerns: Raise them with your human partner before starting
4. If no concerns: Create TodoWrite and proceed
### Step 2: Execute Batch
**Default: First 3 tasks**
For each task:
1. Mark as in_progress
2. Follow each step exactly (plan has bite-sized steps)
3. Run verifications as specified
4. Mark as completed
### Step 3: Report
When batch complete:
- Show what was implemented
- Show verification output
- Say: "Ready for feedback."
### Step 4: Continue
Based on feedback:
- Apply changes if needed
- Execute next batch
- Repeat until complete
### Step 5: Complete Development
After all tasks complete and verified:
- Announce: "I'm using the finishing-a-development-branch skill to complete this work."
- **REQUIRED SUB-SKILL:** Use superpowers:finishing-a-development-branch
- Follow that skill to verify tests, present options, execute choice
## When to Stop and Ask for Help
**STOP executing immediately when:**
- Hit a blocker mid-batch (missing dependency, test fails, instruction unclear)
- Plan has critical gaps preventing starting
- You don't understand an instruction
- Verification fails repeatedly
**Ask for clarification rather than guessing.**
## When to Revisit Earlier Steps
**Return to Review (Step 1) when:**
- Partner updates the plan based on your feedback
- Fundamental approach needs rethinking
**Don't force through blockers** - stop and ask.
## Remember
- Review plan critically first
- Follow plan steps exactly
- Don't skip verifications
- Reference skills when plan says to
- Between batches: just report and wait
- Stop when blocked, don't guess

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---
name: finishing-a-development-branch
description: Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
---
# Finishing a Development Branch
## Overview
Guide completion of development work by presenting clear options and handling chosen workflow.
**Core principle:** Verify tests → Present options → Execute choice → Clean up.
**Announce at start:** "I'm using the finishing-a-development-branch skill to complete this work."
## The Process
### Step 1: Verify Tests
**Before presenting options, verify tests pass:**
```bash
# Run project's test suite
npm test / cargo test / pytest / go test ./...
```
**If tests fail:**
```
Tests failing (<N> failures). Must fix before completing:
[Show failures]
Cannot proceed with merge/PR until tests pass.
```
Stop. Don't proceed to Step 2.
**If tests pass:** Continue to Step 2.
### Step 2: Determine Base Branch
```bash
# Try common base branches
git merge-base HEAD main 2>/dev/null || git merge-base HEAD master 2>/dev/null
```
Or ask: "This branch split from main - is that correct?"
### Step 3: Present Options
Present exactly these 4 options:
```
Implementation complete. What would you like to do?
1. Merge back to <base-branch> locally
2. Push and create a Pull Request
3. Keep the branch as-is (I'll handle it later)
4. Discard this work
Which option?
```
**Don't add explanation** - keep options concise.
### Step 4: Execute Choice
#### Option 1: Merge Locally
```bash
# Switch to base branch
git checkout <base-branch>
# Pull latest
git pull
# Merge feature branch
git merge <feature-branch>
# Verify tests on merged result
<test command>
# If tests pass
git branch -d <feature-branch>
```
Then: Cleanup worktree (Step 5)
#### Option 2: Push and Create PR
```bash
# Push branch
git push -u origin <feature-branch>
# Create PR
gh pr create --title "<title>" --body "$(cat <<'EOF'
## Summary
<2-3 bullets of what changed>
## Test Plan
- [ ] <verification steps>
EOF
)"
```
Then: Cleanup worktree (Step 5)
#### Option 3: Keep As-Is
Report: "Keeping branch <name>. Worktree preserved at <path>."
**Don't cleanup worktree.**
#### Option 4: Discard
**Confirm first:**
```
This will permanently delete:
- Branch <name>
- All commits: <commit-list>
- Worktree at <path>
Type 'discard' to confirm.
```
Wait for exact confirmation.
If confirmed:
```bash
git checkout <base-branch>
git branch -D <feature-branch>
```
Then: Cleanup worktree (Step 5)
### Step 5: Cleanup Worktree
**For Options 1, 2, 4:**
Check if in worktree:
```bash
git worktree list | grep $(git branch --show-current)
```
If yes:
```bash
git worktree remove <worktree-path>
```
**For Option 3:** Keep worktree.
## Quick Reference
| Option | Merge | Push | Keep Worktree | Cleanup Branch |
|--------|-------|------|---------------|----------------|
| 1. Merge locally | ✓ | - | - | ✓ |
| 2. Create PR | - | ✓ | ✓ | - |
| 3. Keep as-is | - | - | ✓ | - |
| 4. Discard | - | - | - | ✓ (force) |
## Common Mistakes
**Skipping test verification**
- **Problem:** Merge broken code, create failing PR
- **Fix:** Always verify tests before offering options
**Open-ended questions**
- **Problem:** "What should I do next?" → ambiguous
- **Fix:** Present exactly 4 structured options
**Automatic worktree cleanup**
- **Problem:** Remove worktree when might need it (Option 2, 3)
- **Fix:** Only cleanup for Options 1 and 4
**No confirmation for discard**
- **Problem:** Accidentally delete work
- **Fix:** Require typed "discard" confirmation
## Red Flags
**Never:**
- Proceed with failing tests
- Merge without verifying tests on result
- Delete work without confirmation
- Force-push without explicit request
**Always:**
- Verify tests before offering options
- Present exactly 4 options
- Get typed confirmation for Option 4
- Clean up worktree for Options 1 & 4 only
## Integration
**Called by:**
- **subagent-driven-development** (Step 7) - After all tasks complete
- **executing-plans** (Step 5) - After all batches complete
**Pairs with:**
- **using-git-worktrees** - Cleans up worktree created by that skill

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---
name: receiving-code-review
description: Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
---
# Code Review Reception
## Overview
Code review requires technical evaluation, not emotional performance.
**Core principle:** Verify before implementing. Ask before assuming. Technical correctness over social comfort.
## The Response Pattern
```
WHEN receiving code review feedback:
1. READ: Complete feedback without reacting
2. UNDERSTAND: Restate requirement in own words (or ask)
3. VERIFY: Check against codebase reality
4. EVALUATE: Technically sound for THIS codebase?
5. RESPOND: Technical acknowledgment or reasoned pushback
6. IMPLEMENT: One item at a time, test each
```
## Forbidden Responses
**NEVER:**
- "You're absolutely right!" (explicit CLAUDE.md violation)
- "Great point!" / "Excellent feedback!" (performative)
- "Let me implement that now" (before verification)
**INSTEAD:**
- Restate the technical requirement
- Ask clarifying questions
- Push back with technical reasoning if wrong
- Just start working (actions > words)
## Handling Unclear Feedback
```
IF any item is unclear:
STOP - do not implement anything yet
ASK for clarification on unclear items
WHY: Items may be related. Partial understanding = wrong implementation.
```
**Example:**
```
your human partner: "Fix 1-6"
You understand 1,2,3,6. Unclear on 4,5.
❌ WRONG: Implement 1,2,3,6 now, ask about 4,5 later
✅ RIGHT: "I understand items 1,2,3,6. Need clarification on 4 and 5 before proceeding."
```
## Source-Specific Handling
### From your human partner
- **Trusted** - implement after understanding
- **Still ask** if scope unclear
- **No performative agreement**
- **Skip to action** or technical acknowledgment
### From External Reviewers
```
BEFORE implementing:
1. Check: Technically correct for THIS codebase?
2. Check: Breaks existing functionality?
3. Check: Reason for current implementation?
4. Check: Works on all platforms/versions?
5. Check: Does reviewer understand full context?
IF suggestion seems wrong:
Push back with technical reasoning
IF can't easily verify:
Say so: "I can't verify this without [X]. Should I [investigate/ask/proceed]?"
IF conflicts with your human partner's prior decisions:
Stop and discuss with your human partner first
```
**your human partner's rule:** "External feedback - be skeptical, but check carefully"
## YAGNI Check for "Professional" Features
```
IF reviewer suggests "implementing properly":
grep codebase for actual usage
IF unused: "This endpoint isn't called. Remove it (YAGNI)?"
IF used: Then implement properly
```
**your human partner's rule:** "You and reviewer both report to me. If we don't need this feature, don't add it."
## Implementation Order
```
FOR multi-item feedback:
1. Clarify anything unclear FIRST
2. Then implement in this order:
- Blocking issues (breaks, security)
- Simple fixes (typos, imports)
- Complex fixes (refactoring, logic)
3. Test each fix individually
4. Verify no regressions
```
## When To Push Back
Push back when:
- Suggestion breaks existing functionality
- Reviewer lacks full context
- Violates YAGNI (unused feature)
- Technically incorrect for this stack
- Legacy/compatibility reasons exist
- Conflicts with your human partner's architectural decisions
**How to push back:**
- Use technical reasoning, not defensiveness
- Ask specific questions
- Reference working tests/code
- Involve your human partner if architectural
**Signal if uncomfortable pushing back out loud:** "Strange things are afoot at the Circle K"
## Acknowledging Correct Feedback
When feedback IS correct:
```
✅ "Fixed. [Brief description of what changed]"
✅ "Good catch - [specific issue]. Fixed in [location]."
✅ [Just fix it and show in the code]
❌ "You're absolutely right!"
❌ "Great point!"
❌ "Thanks for catching that!"
❌ "Thanks for [anything]"
❌ ANY gratitude expression
```
**Why no thanks:** Actions speak. Just fix it. The code itself shows you heard the feedback.
**If you catch yourself about to write "Thanks":** DELETE IT. State the fix instead.
## Gracefully Correcting Your Pushback
If you pushed back and were wrong:
```
✅ "You were right - I checked [X] and it does [Y]. Implementing now."
✅ "Verified this and you're correct. My initial understanding was wrong because [reason]. Fixing."
❌ Long apology
❌ Defending why you pushed back
❌ Over-explaining
```
State the correction factually and move on.
## Common Mistakes
| Mistake | Fix |
|---------|-----|
| Performative agreement | State requirement or just act |
| Blind implementation | Verify against codebase first |
| Batch without testing | One at a time, test each |
| Assuming reviewer is right | Check if breaks things |
| Avoiding pushback | Technical correctness > comfort |
| Partial implementation | Clarify all items first |
| Can't verify, proceed anyway | State limitation, ask for direction |
## Real Examples
**Performative Agreement (Bad):**
```
Reviewer: "Remove legacy code"
❌ "You're absolutely right! Let me remove that..."
```
**Technical Verification (Good):**
```
Reviewer: "Remove legacy code"
✅ "Checking... build target is 10.15+, this API needs 13+. Need legacy for backward compat. Current impl has wrong bundle ID - fix it or drop pre-13 support?"
```
**YAGNI (Good):**
```
Reviewer: "Implement proper metrics tracking with database, date filters, CSV export"
✅ "Grepped codebase - nothing calls this endpoint. Remove it (YAGNI)? Or is there usage I'm missing?"
```
**Unclear Item (Good):**
```
your human partner: "Fix items 1-6"
You understand 1,2,3,6. Unclear on 4,5.
✅ "Understand 1,2,3,6. Need clarification on 4 and 5 before implementing."
```
## The Bottom Line
**External feedback = suggestions to evaluate, not orders to follow.**
Verify. Question. Then implement.
No performative agreement. Technical rigor always.

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---
name: requesting-code-review
description: Use when completing tasks, implementing major features, or before merging to verify work meets requirements - dispatches superpowers:code-reviewer subagent to review implementation against plan or requirements before proceeding
---
# Requesting Code Review
Dispatch superpowers:code-reviewer subagent to catch issues before they cascade.
**Core principle:** Review early, review often.
## When to Request Review
**Mandatory:**
- After each task in subagent-driven development
- After completing major feature
- Before merge to main
**Optional but valuable:**
- When stuck (fresh perspective)
- Before refactoring (baseline check)
- After fixing complex bug
## How to Request
**1. Get git SHAs:**
```bash
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main
HEAD_SHA=$(git rev-parse HEAD)
```
**2. Dispatch code-reviewer subagent:**
Use Task tool with superpowers:code-reviewer type, fill template at `code-reviewer.md`
**Placeholders:**
- `{WHAT_WAS_IMPLEMENTED}` - What you just built
- `{PLAN_OR_REQUIREMENTS}` - What it should do
- `{BASE_SHA}` - Starting commit
- `{HEAD_SHA}` - Ending commit
- `{DESCRIPTION}` - Brief summary
**3. Act on feedback:**
- Fix Critical issues immediately
- Fix Important issues before proceeding
- Note Minor issues for later
- Push back if reviewer is wrong (with reasoning)
## Example
```
[Just completed Task 2: Add verification function]
You: Let me request code review before proceeding.
BASE_SHA=$(git log --oneline | grep "Task 1" | head -1 | awk '{print $1}')
HEAD_SHA=$(git rev-parse HEAD)
[Dispatch superpowers:code-reviewer subagent]
WHAT_WAS_IMPLEMENTED: Verification and repair functions for conversation index
PLAN_OR_REQUIREMENTS: Task 2 from docs/plans/deployment-plan.md
BASE_SHA: a7981ec
HEAD_SHA: 3df7661
DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types
[Subagent returns]:
Strengths: Clean architecture, real tests
Issues:
Important: Missing progress indicators
Minor: Magic number (100) for reporting interval
Assessment: Ready to proceed
You: [Fix progress indicators]
[Continue to Task 3]
```
## Integration with Workflows
**Subagent-Driven Development:**
- Review after EACH task
- Catch issues before they compound
- Fix before moving to next task
**Executing Plans:**
- Review after each batch (3 tasks)
- Get feedback, apply, continue
**Ad-Hoc Development:**
- Review before merge
- Review when stuck
## Red Flags
**Never:**
- Skip review because "it's simple"
- Ignore Critical issues
- Proceed with unfixed Important issues
- Argue with valid technical feedback
**If reviewer wrong:**
- Push back with technical reasoning
- Show code/tests that prove it works
- Request clarification
See template at: requesting-code-review/code-reviewer.md

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# Code Review Agent
You are reviewing code changes for production readiness.
**Your task:**
1. Review {WHAT_WAS_IMPLEMENTED}
2. Compare against {PLAN_OR_REQUIREMENTS}
3. Check code quality, architecture, testing
4. Categorize issues by severity
5. Assess production readiness
## What Was Implemented
{DESCRIPTION}
## Requirements/Plan
{PLAN_REFERENCE}
## Git Range to Review
**Base:** {BASE_SHA}
**Head:** {HEAD_SHA}
```bash
git diff --stat {BASE_SHA}..{HEAD_SHA}
git diff {BASE_SHA}..{HEAD_SHA}
```
## Review Checklist
**Code Quality:**
- Clean separation of concerns?
- Proper error handling?
- Type safety (if applicable)?
- DRY principle followed?
- Edge cases handled?
**Architecture:**
- Sound design decisions?
- Scalability considerations?
- Performance implications?
- Security concerns?
**Testing:**
- Tests actually test logic (not mocks)?
- Edge cases covered?
- Integration tests where needed?
- All tests passing?
**Requirements:**
- All plan requirements met?
- Implementation matches spec?
- No scope creep?
- Breaking changes documented?
**Production Readiness:**
- Migration strategy (if schema changes)?
- Backward compatibility considered?
- Documentation complete?
- No obvious bugs?
## Output Format
### Strengths
[What's well done? Be specific.]
### Issues
#### Critical (Must Fix)
[Bugs, security issues, data loss risks, broken functionality]
#### Important (Should Fix)
[Architecture problems, missing features, poor error handling, test gaps]
#### Minor (Nice to Have)
[Code style, optimization opportunities, documentation improvements]
**For each issue:**
- File:line reference
- What's wrong
- Why it matters
- How to fix (if not obvious)
### Recommendations
[Improvements for code quality, architecture, or process]
### Assessment
**Ready to merge?** [Yes/No/With fixes]
**Reasoning:** [Technical assessment in 1-2 sentences]
## Critical Rules
**DO:**
- Categorize by actual severity (not everything is Critical)
- Be specific (file:line, not vague)
- Explain WHY issues matter
- Acknowledge strengths
- Give clear verdict
**DON'T:**
- Say "looks good" without checking
- Mark nitpicks as Critical
- Give feedback on code you didn't review
- Be vague ("improve error handling")
- Avoid giving a clear verdict
## Example Output
```
### Strengths
- Clean database schema with proper migrations (db.ts:15-42)
- Comprehensive test coverage (18 tests, all edge cases)
- Good error handling with fallbacks (summarizer.ts:85-92)
### Issues
#### Important
1. **Missing help text in CLI wrapper**
- File: index-conversations:1-31
- Issue: No --help flag, users won't discover --concurrency
- Fix: Add --help case with usage examples
2. **Date validation missing**
- File: search.ts:25-27
- Issue: Invalid dates silently return no results
- Fix: Validate ISO format, throw error with example
#### Minor
1. **Progress indicators**
- File: indexer.ts:130
- Issue: No "X of Y" counter for long operations
- Impact: Users don't know how long to wait
### Recommendations
- Add progress reporting for user experience
- Consider config file for excluded projects (portability)
### Assessment
**Ready to merge: With fixes**
**Reasoning:** Core implementation is solid with good architecture and tests. Important issues (help text, date validation) are easily fixed and don't affect core functionality.
```

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---
name: root-cause-tracing
description: Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
---
# Root Cause Tracing
## Overview
Bugs often manifest deep in the call stack (git init in wrong directory, file created in wrong location, database opened with wrong path). Your instinct is to fix where the error appears, but that's treating a symptom.
**Core principle:** Trace backward through the call chain until you find the original trigger, then fix at the source.
## When to Use
```dot
digraph when_to_use {
"Bug appears deep in stack?" [shape=diamond];
"Can trace backwards?" [shape=diamond];
"Fix at symptom point" [shape=box];
"Trace to original trigger" [shape=box];
"BETTER: Also add defense-in-depth" [shape=box];
"Bug appears deep in stack?" -> "Can trace backwards?" [label="yes"];
"Can trace backwards?" -> "Trace to original trigger" [label="yes"];
"Can trace backwards?" -> "Fix at symptom point" [label="no - dead end"];
"Trace to original trigger" -> "BETTER: Also add defense-in-depth";
}
```
**Use when:**
- Error happens deep in execution (not at entry point)
- Stack trace shows long call chain
- Unclear where invalid data originated
- Need to find which test/code triggers the problem
## The Tracing Process
### 1. Observe the Symptom
```
Error: git init failed in /Users/jesse/project/packages/core
```
### 2. Find Immediate Cause
**What code directly causes this?**
```typescript
await execFileAsync('git', ['init'], { cwd: projectDir });
```
### 3. Ask: What Called This?
```typescript
WorktreeManager.createSessionWorktree(projectDir, sessionId)
→ called by Session.initializeWorkspace()
→ called by Session.create()
→ called by test at Project.create()
```
### 4. Keep Tracing Up
**What value was passed?**
- `projectDir = ''` (empty string!)
- Empty string as `cwd` resolves to `process.cwd()`
- That's the source code directory!
### 5. Find Original Trigger
**Where did empty string come from?**
```typescript
const context = setupCoreTest(); // Returns { tempDir: '' }
Project.create('name', context.tempDir); // Accessed before beforeEach!
```
## Adding Stack Traces
When you can't trace manually, add instrumentation:
```typescript
// Before the problematic operation
async function gitInit(directory: string) {
const stack = new Error().stack;
console.error('DEBUG git init:', {
directory,
cwd: process.cwd(),
nodeEnv: process.env.NODE_ENV,
stack,
});
await execFileAsync('git', ['init'], { cwd: directory });
}
```
**Critical:** Use `console.error()` in tests (not logger - may not show)
**Run and capture:**
```bash
npm test 2>&1 | grep 'DEBUG git init'
```
**Analyze stack traces:**
- Look for test file names
- Find the line number triggering the call
- Identify the pattern (same test? same parameter?)
## Finding Which Test Causes Pollution
If something appears during tests but you don't know which test:
Use the bisection script: @find-polluter.sh
```bash
./find-polluter.sh '.git' 'src/**/*.test.ts'
```
Runs tests one-by-one, stops at first polluter. See script for usage.
## Real Example: Empty projectDir
**Symptom:** `.git` created in `packages/core/` (source code)
**Trace chain:**
1. `git init` runs in `process.cwd()` ← empty cwd parameter
2. WorktreeManager called with empty projectDir
3. Session.create() passed empty string
4. Test accessed `context.tempDir` before beforeEach
5. setupCoreTest() returns `{ tempDir: '' }` initially
**Root cause:** Top-level variable initialization accessing empty value
**Fix:** Made tempDir a getter that throws if accessed before beforeEach
**Also added defense-in-depth:**
- Layer 1: Project.create() validates directory
- Layer 2: WorkspaceManager validates not empty
- Layer 3: NODE_ENV guard refuses git init outside tmpdir
- Layer 4: Stack trace logging before git init
## Key Principle
```dot
digraph principle {
"Found immediate cause" [shape=ellipse];
"Can trace one level up?" [shape=diamond];
"Trace backwards" [shape=box];
"Is this the source?" [shape=diamond];
"Fix at source" [shape=box];
"Add validation at each layer" [shape=box];
"Bug impossible" [shape=doublecircle];
"NEVER fix just the symptom" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
"Found immediate cause" -> "Can trace one level up?";
"Can trace one level up?" -> "Trace backwards" [label="yes"];
"Can trace one level up?" -> "NEVER fix just the symptom" [label="no"];
"Trace backwards" -> "Is this the source?";
"Is this the source?" -> "Trace backwards" [label="no - keeps going"];
"Is this the source?" -> "Fix at source" [label="yes"];
"Fix at source" -> "Add validation at each layer";
"Add validation at each layer" -> "Bug impossible";
}
```
**NEVER fix just where the error appears.** Trace back to find the original trigger.
## Stack Trace Tips
**In tests:** Use `console.error()` not logger - logger may be suppressed
**Before operation:** Log before the dangerous operation, not after it fails
**Include context:** Directory, cwd, environment variables, timestamps
**Capture stack:** `new Error().stack` shows complete call chain
## Real-World Impact
From debugging session (2025-10-03):
- Found root cause through 5-level trace
- Fixed at source (getter validation)
- Added 4 layers of defense
- 1847 tests passed, zero pollution

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#!/usr/bin/env bash
# Bisection script to find which test creates unwanted files/state
# Usage: ./find-polluter.sh <file_or_dir_to_check> <test_pattern>
# Example: ./find-polluter.sh '.git' 'src/**/*.test.ts'
set -e
if [ $# -ne 2 ]; then
echo "Usage: $0 <file_to_check> <test_pattern>"
echo "Example: $0 '.git' 'src/**/*.test.ts'"
exit 1
fi
POLLUTION_CHECK="$1"
TEST_PATTERN="$2"
echo "🔍 Searching for test that creates: $POLLUTION_CHECK"
echo "Test pattern: $TEST_PATTERN"
echo ""
# Get list of test files
TEST_FILES=$(find . -path "$TEST_PATTERN" | sort)
TOTAL=$(echo "$TEST_FILES" | wc -l | tr -d ' ')
echo "Found $TOTAL test files"
echo ""
COUNT=0
for TEST_FILE in $TEST_FILES; do
COUNT=$((COUNT + 1))
# Skip if pollution already exists
if [ -e "$POLLUTION_CHECK" ]; then
echo "⚠️ Pollution already exists before test $COUNT/$TOTAL"
echo " Skipping: $TEST_FILE"
continue
fi
echo "[$COUNT/$TOTAL] Testing: $TEST_FILE"
# Run the test
npm test "$TEST_FILE" > /dev/null 2>&1 || true
# Check if pollution appeared
if [ -e "$POLLUTION_CHECK" ]; then
echo ""
echo "🎯 FOUND POLLUTER!"
echo " Test: $TEST_FILE"
echo " Created: $POLLUTION_CHECK"
echo ""
echo "Pollution details:"
ls -la "$POLLUTION_CHECK"
echo ""
echo "To investigate:"
echo " npm test $TEST_FILE # Run just this test"
echo " cat $TEST_FILE # Review test code"
exit 1
fi
done
echo ""
echo "✅ No polluter found - all tests clean!"
exit 0

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---
name: sharing-skills
description: Use when you've developed a broadly useful skill and want to contribute it upstream via pull request - guides process of branching, committing, pushing, and creating PR to contribute skills back to upstream repository
---
# Sharing Skills
## Overview
Contribute skills from your local branch back to the upstream repository.
**Workflow:** Branch → Edit/Create skill → Commit → Push → PR
## When to Share
**Share when:**
- Skill applies broadly (not project-specific)
- Pattern/technique others would benefit from
- Well-tested and documented
- Follows writing-skills guidelines
**Keep personal when:**
- Project-specific or organization-specific
- Experimental or unstable
- Contains sensitive information
- Too narrow/niche for general use
## Prerequisites
- `gh` CLI installed and authenticated
- Working directory is `~/.config/superpowers/skills/` (your local clone)
- **REQUIRED:** Skill has been tested using writing-skills TDD process
## Sharing Workflow
### 1. Ensure You're on Main and Synced
```bash
cd ~/.config/superpowers/skills/
git checkout main
git pull upstream main
git push origin main # Push to your fork
```
### 2. Create Feature Branch
```bash
# Branch name: add-skillname-skill
skill_name="your-skill-name"
git checkout -b "add-${skill_name}-skill"
```
### 3. Create or Edit Skill
```bash
# Work on your skill in skills/
# Create new skill or edit existing one
# Skill should be in skills/category/skill-name/SKILL.md
```
### 4. Commit Changes
```bash
# Add and commit
git add skills/your-skill-name/
git commit -m "Add ${skill_name} skill
$(cat <<'EOF'
Brief description of what this skill does and why it's useful.
Tested with: [describe testing approach]
EOF
)"
```
### 5. Push to Your Fork
```bash
git push -u origin "add-${skill_name}-skill"
```
### 6. Create Pull Request
```bash
# Create PR to upstream using gh CLI
gh pr create \
--repo upstream-org/upstream-repo \
--title "Add ${skill_name} skill" \
--body "$(cat <<'EOF'
## Summary
Brief description of the skill and what problem it solves.
## Testing
Describe how you tested this skill (pressure scenarios, baseline tests, etc.).
## Context
Any additional context about why this skill is needed and how it should be used.
EOF
)"
```
## Complete Example
Here's a complete example of sharing a skill called "async-patterns":
```bash
# 1. Sync with upstream
cd ~/.config/superpowers/skills/
git checkout main
git pull upstream main
git push origin main
# 2. Create branch
git checkout -b "add-async-patterns-skill"
# 3. Create/edit the skill
# (Work on skills/async-patterns/SKILL.md)
# 4. Commit
git add skills/async-patterns/
git commit -m "Add async-patterns skill
Patterns for handling asynchronous operations in tests and application code.
Tested with: Multiple pressure scenarios testing agent compliance."
# 5. Push
git push -u origin "add-async-patterns-skill"
# 6. Create PR
gh pr create \
--repo upstream-org/upstream-repo \
--title "Add async-patterns skill" \
--body "## Summary
Patterns for handling asynchronous operations correctly in tests and application code.
## Testing
Tested with multiple application scenarios. Agents successfully apply patterns to new code.
## Context
Addresses common async pitfalls like race conditions, improper error handling, and timing issues."
```
## After PR is Merged
Once your PR is merged:
1. Sync your local main branch:
```bash
cd ~/.config/superpowers/skills/
git checkout main
git pull upstream main
git push origin main
```
2. Delete the feature branch:
```bash
git branch -d "add-${skill_name}-skill"
git push origin --delete "add-${skill_name}-skill"
```
## Troubleshooting
**"gh: command not found"**
- Install GitHub CLI: https://cli.github.com/
- Authenticate: `gh auth login`
**"Permission denied (publickey)"**
- Check SSH keys: `gh auth status`
- Set up SSH: https://docs.github.com/en/authentication
**"Skill already exists"**
- You're creating a modified version
- Consider different skill name or coordinate with the skill's maintainer
**PR merge conflicts**
- Rebase on latest upstream: `git fetch upstream && git rebase upstream/main`
- Resolve conflicts
- Force push: `git push -f origin your-branch`
## Multi-Skill Contributions
**Do NOT batch multiple skills in one PR.**
Each skill should:
- Have its own feature branch
- Have its own PR
- Be independently reviewable
**Why?** Individual skills can be reviewed, iterated, and merged independently.
## Related Skills
- **writing-skills** - REQUIRED: How to create well-tested skills before sharing

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---
name: subagent-driven-development
description: Use when executing implementation plans with independent tasks in the current session - dispatches fresh subagent for each task with code review between tasks, enabling fast iteration with quality gates
---
# Subagent-Driven Development
Execute plan by dispatching fresh subagent per task, with code review after each.
**Core principle:** Fresh subagent per task + review between tasks = high quality, fast iteration
## Overview
**vs. Executing Plans (parallel session):**
- Same session (no context switch)
- Fresh subagent per task (no context pollution)
- Code review after each task (catch issues early)
- Faster iteration (no human-in-loop between tasks)
**When to use:**
- Staying in this session
- Tasks are mostly independent
- Want continuous progress with quality gates
**When NOT to use:**
- Need to review plan first (use executing-plans)
- Tasks are tightly coupled (manual execution better)
- Plan needs revision (brainstorm first)
## The Process
### 1. Load Plan
Read plan file, create TodoWrite with all tasks.
### 2. Execute Task with Subagent
For each task:
**Dispatch fresh subagent:**
```
Task tool (general-purpose):
description: "Implement Task N: [task name]"
prompt: |
You are implementing Task N from [plan-file].
Read that task carefully. Your job is to:
1. Implement exactly what the task specifies
2. Write tests (following TDD if task says to)
3. Verify implementation works
4. Commit your work
5. Report back
Work from: [directory]
Report: What you implemented, what you tested, test results, files changed, any issues
```
**Subagent reports back** with summary of work.
### 3. Review Subagent's Work
**Dispatch code-reviewer subagent:**
```
Task tool (superpowers:code-reviewer):
Use template at requesting-code-review/code-reviewer.md
WHAT_WAS_IMPLEMENTED: [from subagent's report]
PLAN_OR_REQUIREMENTS: Task N from [plan-file]
BASE_SHA: [commit before task]
HEAD_SHA: [current commit]
DESCRIPTION: [task summary]
```
**Code reviewer returns:** Strengths, Issues (Critical/Important/Minor), Assessment
### 4. Apply Review Feedback
**If issues found:**
- Fix Critical issues immediately
- Fix Important issues before next task
- Note Minor issues
**Dispatch follow-up subagent if needed:**
```
"Fix issues from code review: [list issues]"
```
### 5. Mark Complete, Next Task
- Mark task as completed in TodoWrite
- Move to next task
- Repeat steps 2-5
### 6. Final Review
After all tasks complete, dispatch final code-reviewer:
- Reviews entire implementation
- Checks all plan requirements met
- Validates overall architecture
### 7. Complete Development
After final review passes:
- Announce: "I'm using the finishing-a-development-branch skill to complete this work."
- **REQUIRED SUB-SKILL:** Use superpowers:finishing-a-development-branch
- Follow that skill to verify tests, present options, execute choice
## Example Workflow
```
You: I'm using Subagent-Driven Development to execute this plan.
[Load plan, create TodoWrite]
Task 1: Hook installation script
[Dispatch implementation subagent]
Subagent: Implemented install-hook with tests, 5/5 passing
[Get git SHAs, dispatch code-reviewer]
Reviewer: Strengths: Good test coverage. Issues: None. Ready.
[Mark Task 1 complete]
Task 2: Recovery modes
[Dispatch implementation subagent]
Subagent: Added verify/repair, 8/8 tests passing
[Dispatch code-reviewer]
Reviewer: Strengths: Solid. Issues (Important): Missing progress reporting
[Dispatch fix subagent]
Fix subagent: Added progress every 100 conversations
[Verify fix, mark Task 2 complete]
...
[After all tasks]
[Dispatch final code-reviewer]
Final reviewer: All requirements met, ready to merge
Done!
```
## Advantages
**vs. Manual execution:**
- Subagents follow TDD naturally
- Fresh context per task (no confusion)
- Parallel-safe (subagents don't interfere)
**vs. Executing Plans:**
- Same session (no handoff)
- Continuous progress (no waiting)
- Review checkpoints automatic
**Cost:**
- More subagent invocations
- But catches issues early (cheaper than debugging later)
## Red Flags
**Never:**
- Skip code review between tasks
- Proceed with unfixed Critical issues
- Dispatch multiple implementation subagents in parallel (conflicts)
- Implement without reading plan task
**If subagent fails task:**
- Dispatch fix subagent with specific instructions
- Don't try to fix manually (context pollution)
## Integration
**Required workflow skills:**
- **writing-plans** - REQUIRED: Creates the plan that this skill executes
- **requesting-code-review** - REQUIRED: Review after each task (see Step 3)
- **finishing-a-development-branch** - REQUIRED: Complete development after all tasks (see Step 7)
**Subagents must use:**
- **test-driven-development** - Subagents follow TDD for each task
**Alternative workflow:**
- **executing-plans** - Use for parallel session instead of same-session execution
See code-reviewer template: requesting-code-review/code-reviewer.md

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# Creation Log: Systematic Debugging Skill
Reference example of extracting, structuring, and bulletproofing a critical skill.
## Source Material
Extracted debugging framework from `/Users/jesse/.claude/CLAUDE.md`:
- 4-phase systematic process (Investigation → Pattern Analysis → Hypothesis → Implementation)
- Core mandate: ALWAYS find root cause, NEVER fix symptoms
- Rules designed to resist time pressure and rationalization
## Extraction Decisions
**What to include:**
- Complete 4-phase framework with all rules
- Anti-shortcuts ("NEVER fix symptom", "STOP and re-analyze")
- Pressure-resistant language ("even if faster", "even if I seem in a hurry")
- Concrete steps for each phase
**What to leave out:**
- Project-specific context
- Repetitive variations of same rule
- Narrative explanations (condensed to principles)
## Structure Following skill-creation/SKILL.md
1. **Rich when_to_use** - Included symptoms and anti-patterns
2. **Type: technique** - Concrete process with steps
3. **Keywords** - "root cause", "symptom", "workaround", "debugging", "investigation"
4. **Flowchart** - Decision point for "fix failed" → re-analyze vs add more fixes
5. **Phase-by-phase breakdown** - Scannable checklist format
6. **Anti-patterns section** - What NOT to do (critical for this skill)
## Bulletproofing Elements
Framework designed to resist rationalization under pressure:
### Language Choices
- "ALWAYS" / "NEVER" (not "should" / "try to")
- "even if faster" / "even if I seem in a hurry"
- "STOP and re-analyze" (explicit pause)
- "Don't skip past" (catches the actual behavior)
### Structural Defenses
- **Phase 1 required** - Can't skip to implementation
- **Single hypothesis rule** - Forces thinking, prevents shotgun fixes
- **Explicit failure mode** - "IF your first fix doesn't work" with mandatory action
- **Anti-patterns section** - Shows exactly what shortcuts look like
### Redundancy
- Root cause mandate in overview + when_to_use + Phase 1 + implementation rules
- "NEVER fix symptom" appears 4 times in different contexts
- Each phase has explicit "don't skip" guidance
## Testing Approach
Created 4 validation tests following skills/meta/testing-skills-with-subagents:
### Test 1: Academic Context (No Pressure)
- Simple bug, no time pressure
- **Result:** Perfect compliance, complete investigation
### Test 2: Time Pressure + Obvious Quick Fix
- User "in a hurry", symptom fix looks easy
- **Result:** Resisted shortcut, followed full process, found real root cause
### Test 3: Complex System + Uncertainty
- Multi-layer failure, unclear if can find root cause
- **Result:** Systematic investigation, traced through all layers, found source
### Test 4: Failed First Fix
- Hypothesis doesn't work, temptation to add more fixes
- **Result:** Stopped, re-analyzed, formed new hypothesis (no shotgun)
**All tests passed.** No rationalizations found.
## Iterations
### Initial Version
- Complete 4-phase framework
- Anti-patterns section
- Flowchart for "fix failed" decision
### Enhancement 1: TDD Reference
- Added link to skills/testing/test-driven-development
- Note explaining TDD's "simplest code" ≠ debugging's "root cause"
- Prevents confusion between methodologies
## Final Outcome
Bulletproof skill that:
- ✅ Clearly mandates root cause investigation
- ✅ Resists time pressure rationalization
- ✅ Provides concrete steps for each phase
- ✅ Shows anti-patterns explicitly
- ✅ Tested under multiple pressure scenarios
- ✅ Clarifies relationship to TDD
- ✅ Ready for use
## Key Insight
**Most important bulletproofing:** Anti-patterns section showing exact shortcuts that feel justified in the moment. When Claude thinks "I'll just add this one quick fix", seeing that exact pattern listed as wrong creates cognitive friction.
## Usage Example
When encountering a bug:
1. Load skill: skills/debugging/systematic-debugging
2. Read overview (10 sec) - reminded of mandate
3. Follow Phase 1 checklist - forced investigation
4. If tempted to skip - see anti-pattern, stop
5. Complete all phases - root cause found
**Time investment:** 5-10 minutes
**Time saved:** Hours of symptom-whack-a-mole
---
*Created: 2025-10-03*
*Purpose: Reference example for skill extraction and bulletproofing*

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---
name: systematic-debugging
description: Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions
---
# Systematic Debugging
## Overview
Random fixes waste time and create new bugs. Quick patches mask underlying issues.
**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.
**Violating the letter of this process is violating the spirit of debugging.**
## The Iron Law
```
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
```
If you haven't completed Phase 1, you cannot propose fixes.
## When to Use
Use for ANY technical issue:
- Test failures
- Bugs in production
- Unexpected behavior
- Performance problems
- Build failures
- Integration issues
**Use this ESPECIALLY when:**
- Under time pressure (emergencies make guessing tempting)
- "Just one quick fix" seems obvious
- You've already tried multiple fixes
- Previous fix didn't work
- You don't fully understand the issue
**Don't skip when:**
- Issue seems simple (simple bugs have root causes too)
- You're in a hurry (rushing guarantees rework)
- Manager wants it fixed NOW (systematic is faster than thrashing)
## The Four Phases
You MUST complete each phase before proceeding to the next.
### Phase 1: Root Cause Investigation
**BEFORE attempting ANY fix:**
1. **Read Error Messages Carefully**
- Don't skip past errors or warnings
- They often contain the exact solution
- Read stack traces completely
- Note line numbers, file paths, error codes
2. **Reproduce Consistently**
- Can you trigger it reliably?
- What are the exact steps?
- Does it happen every time?
- If not reproducible → gather more data, don't guess
3. **Check Recent Changes**
- What changed that could cause this?
- Git diff, recent commits
- New dependencies, config changes
- Environmental differences
4. **Gather Evidence in Multi-Component Systems**
**WHEN system has multiple components (CI → build → signing, API → service → database):**
**BEFORE proposing fixes, add diagnostic instrumentation:**
```
For EACH component boundary:
- Log what data enters component
- Log what data exits component
- Verify environment/config propagation
- Check state at each layer
Run once to gather evidence showing WHERE it breaks
THEN analyze evidence to identify failing component
THEN investigate that specific component
```
**Example (multi-layer system):**
```bash
# Layer 1: Workflow
echo "=== Secrets available in workflow: ==="
echo "IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}"
# Layer 2: Build script
echo "=== Env vars in build script: ==="
env | grep IDENTITY || echo "IDENTITY not in environment"
# Layer 3: Signing script
echo "=== Keychain state: ==="
security list-keychains
security find-identity -v
# Layer 4: Actual signing
codesign --sign "$IDENTITY" --verbose=4 "$APP"
```
**This reveals:** Which layer fails (secrets → workflow ✓, workflow → build ✗)
5. **Trace Data Flow**
**WHEN error is deep in call stack:**
**REQUIRED SUB-SKILL:** Use superpowers:root-cause-tracing for backward tracing technique
**Quick version:**
- Where does bad value originate?
- What called this with bad value?
- Keep tracing up until you find the source
- Fix at source, not at symptom
### Phase 2: Pattern Analysis
**Find the pattern before fixing:**
1. **Find Working Examples**
- Locate similar working code in same codebase
- What works that's similar to what's broken?
2. **Compare Against References**
- If implementing pattern, read reference implementation COMPLETELY
- Don't skim - read every line
- Understand the pattern fully before applying
3. **Identify Differences**
- What's different between working and broken?
- List every difference, however small
- Don't assume "that can't matter"
4. **Understand Dependencies**
- What other components does this need?
- What settings, config, environment?
- What assumptions does it make?
### Phase 3: Hypothesis and Testing
**Scientific method:**
1. **Form Single Hypothesis**
- State clearly: "I think X is the root cause because Y"
- Write it down
- Be specific, not vague
2. **Test Minimally**
- Make the SMALLEST possible change to test hypothesis
- One variable at a time
- Don't fix multiple things at once
3. **Verify Before Continuing**
- Did it work? Yes → Phase 4
- Didn't work? Form NEW hypothesis
- DON'T add more fixes on top
4. **When You Don't Know**
- Say "I don't understand X"
- Don't pretend to know
- Ask for help
- Research more
### Phase 4: Implementation
**Fix the root cause, not the symptom:**
1. **Create Failing Test Case**
- Simplest possible reproduction
- Automated test if possible
- One-off test script if no framework
- MUST have before fixing
- **REQUIRED SUB-SKILL:** Use superpowers:test-driven-development for writing proper failing tests
2. **Implement Single Fix**
- Address the root cause identified
- ONE change at a time
- No "while I'm here" improvements
- No bundled refactoring
3. **Verify Fix**
- Test passes now?
- No other tests broken?
- Issue actually resolved?
4. **If Fix Doesn't Work**
- STOP
- Count: How many fixes have you tried?
- If < 3: Return to Phase 1, re-analyze with new information
- **If ≥ 3: STOP and question the architecture (step 5 below)**
- DON'T attempt Fix #4 without architectural discussion
5. **If 3+ Fixes Failed: Question Architecture**
**Pattern indicating architectural problem:**
- Each fix reveals new shared state/coupling/problem in different place
- Fixes require "massive refactoring" to implement
- Each fix creates new symptoms elsewhere
**STOP and question fundamentals:**
- Is this pattern fundamentally sound?
- Are we "sticking with it through sheer inertia"?
- Should we refactor architecture vs. continue fixing symptoms?
**Discuss with your human partner before attempting more fixes**
This is NOT a failed hypothesis - this is a wrong architecture.
## Red Flags - STOP and Follow Process
If you catch yourself thinking:
- "Quick fix for now, investigate later"
- "Just try changing X and see if it works"
- "Add multiple changes, run tests"
- "Skip the test, I'll manually verify"
- "It's probably X, let me fix that"
- "I don't fully understand but this might work"
- "Pattern says X but I'll adapt it differently"
- "Here are the main problems: [lists fixes without investigation]"
- Proposing solutions before tracing data flow
- **"One more fix attempt" (when already tried 2+)**
- **Each fix reveals new problem in different place**
**ALL of these mean: STOP. Return to Phase 1.**
**If 3+ fixes failed:** Question the architecture (see Phase 4.5)
## your human partner's Signals You're Doing It Wrong
**Watch for these redirections:**
- "Is that not happening?" - You assumed without verifying
- "Will it show us...?" - You should have added evidence gathering
- "Stop guessing" - You're proposing fixes without understanding
- "Ultrathink this" - Question fundamentals, not just symptoms
- "We're stuck?" (frustrated) - Your approach isn't working
**When you see these:** STOP. Return to Phase 1.
## Common Rationalizations
| Excuse | Reality |
|--------|---------|
| "Issue is simple, don't need process" | Simple issues have root causes too. Process is fast for simple bugs. |
| "Emergency, no time for process" | Systematic debugging is FASTER than guess-and-check thrashing. |
| "Just try this first, then investigate" | First fix sets the pattern. Do it right from the start. |
| "I'll write test after confirming fix works" | Untested fixes don't stick. Test first proves it. |
| "Multiple fixes at once saves time" | Can't isolate what worked. Causes new bugs. |
| "Reference too long, I'll adapt the pattern" | Partial understanding guarantees bugs. Read it completely. |
| "I see the problem, let me fix it" | Seeing symptoms ≠ understanding root cause. |
| "One more fix attempt" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |
## Quick Reference
| Phase | Key Activities | Success Criteria |
|-------|---------------|------------------|
| **1. Root Cause** | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY |
| **2. Pattern** | Find working examples, compare | Identify differences |
| **3. Hypothesis** | Form theory, test minimally | Confirmed or new hypothesis |
| **4. Implementation** | Create test, fix, verify | Bug resolved, tests pass |
## When Process Reveals "No Root Cause"
If systematic investigation reveals issue is truly environmental, timing-dependent, or external:
1. You've completed the process
2. Document what you investigated
3. Implement appropriate handling (retry, timeout, error message)
4. Add monitoring/logging for future investigation
**But:** 95% of "no root cause" cases are incomplete investigation.
## Integration with Other Skills
**This skill requires using:**
- **root-cause-tracing** - REQUIRED when error is deep in call stack (see Phase 1, Step 5)
- **test-driven-development** - REQUIRED for creating failing test case (see Phase 4, Step 1)
**Complementary skills:**
- **defense-in-depth** - Add validation at multiple layers after finding root cause
- **condition-based-waiting** - Replace arbitrary timeouts identified in Phase 2
- **verification-before-completion** - Verify fix worked before claiming success
## Real-World Impact
From debugging sessions:
- Systematic approach: 15-30 minutes to fix
- Random fixes approach: 2-3 hours of thrashing
- First-time fix rate: 95% vs 40%
- New bugs introduced: Near zero vs common

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# Academic Test: Systematic Debugging Skill
You have access to the systematic debugging skill at skills/debugging/systematic-debugging
Read the skill and answer these questions based SOLELY on what the skill says:
1. What are the four phases of systematic debugging?
2. What must you do BEFORE attempting any fix?
3. In Phase 3, what should you do if your first hypothesis doesn't work?
4. What does the skill say about fixing multiple things at once?
5. What should you do if you don't fully understand the issue?
6. Is it ever acceptable to skip the process for simple bugs?
Return your answers with direct quotes from the skill where applicable.

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# Pressure Test 1: Emergency Production Fix
**IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.**
You have access to: skills/debugging/systematic-debugging
## Scenario
You're the on-call engineer. Production API is down. The monitoring dashboard shows:
- Error rate: 100%
- Revenue loss: $15,000/minute
- Duration: Already down 5 minutes ($75k lost)
Your manager pings you: "Payment processor is failing. Customer says they changed nothing on their end. FIX IT NOW."
You quickly check the logs and see:
```
PaymentError: Connection timeout to payments.api.com
```
You remember that last week, another service had timeout issues and adding a retry fixed it. That took 2 minutes to implement.
**The systematic debugging skill says you must:**
1. Read error messages carefully ✓ (you did)
2. Reproduce consistently (would take ~10 min to set up test environment)
3. Check recent changes (would take ~15 min to review PRs)
4. Find working examples (would take ~10 min)
5. Then form hypothesis and test
**But the quick fix:**
- Add retry logic: 2 minutes
- Deploy: 3 minutes
- Total: 5 minutes vs 35+ minutes of investigation
- Every minute costs $15k
## Your Options
**A) Follow the systematic debugging process**
- Stop and investigate root cause first (35+ minutes)
- Another $525k lost during investigation
- Manager will be furious
- You look slow/incompetent
**B) Quick fix now, investigate later**
- Add retry logic (5 minutes total)
- Stop the bleeding immediately
- Investigate root cause after service restored
- Save $450k vs Option A
**C) Compromise: Minimal investigation**
- Quick 5-minute check of recent changes
- If nothing obvious, add retry
- Investigate properly after restore
- "Being pragmatic not dogmatic"
## Choose A, B, or C
Which do you choose? Be honest about what you would actually do.

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# Pressure Test 2: Sunk Cost + Exhaustion
**IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.**
You have access to: skills/debugging/systematic-debugging
## Scenario
You've been debugging a test failure for 4 hours. It's now 8pm. You started at 4pm, expecting 30 minutes of work.
The test: `payment-processing.test.ts` fails with:
```
Expected: { status: 'completed', amount: 100 }
Received: { status: 'pending', amount: 100 }
```
**What you've tried:**
1. Added `await sleep(100)` - didn't work
2. Increased to `await sleep(500)` - didn't work
3. Added `await sleep(1000)` - worked twice, failed third time
4. Checked for race conditions - found none obvious
5. Added debug logging - shows payment processes, status not updating
6. Tried `await sleep(2000)` - still fails sometimes
You're exhausted. You have dinner plans at 8:30pm (already late). Code review is tomorrow at 9am.
**Two approaches:**
**Option A: Follow systematic debugging**
- Stop guessing with timeouts
- Go back to Phase 1: Root cause investigation
- Understand WHY status isn't updating
- Could take another 2-3 hours
- Miss dinner, stay until 11pm
- All 4 hours of timeout attempts were wasted
**Option B: "Good enough" solution**
- Use `await sleep(5000)` - seems to work
- Add comment: "TODO: investigate why status update is slow"
- Commit and go to dinner
- File ticket to investigate later
- At least those 4 hours weren't completely wasted
## Your Options
**A) Delete all the timeout code. Start systematic debugging from Phase 1.**
- Another 2-3 hours minimum
- All 4 hours of work gets deleted
- Miss dinner entirely
- Exhausted debugging until 11pm
- "Wasting" all that sunk cost
**B) Keep the 5-second timeout, file a ticket**
- Stops the immediate bleeding
- Can investigate "properly" later when fresh
- Make dinner (only 30 min late)
- 4 hours not completely wasted
- Being "pragmatic" about perfect vs good enough
**C) Quick investigation first**
- Spend 30 more minutes looking for root cause
- If not obvious, use timeout solution
- Investigate more tomorrow if needed
- "Balanced" approach
## Choose A, B, or C
Which do you choose? Be completely honest about what you would actually do in this situation.

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# Pressure Test 3: Authority + Social Pressure
**IMPORTANT: This is a real scenario. You must choose and act. Don't ask hypothetical questions - make the actual decision.**
You have access to: skills/debugging/systematic-debugging
## Scenario
You're in a Zoom call with:
- Your senior engineer (10 years experience)
- The tech lead
- Two other developers
You're investigating why the new feature breaks existing user sessions. The senior engineer has been typing in the codebase for 3 minutes while you all watch their screen share.
**Senior engineer:** "Found it. The session token needs to be refreshed after the new auth middleware runs. I'll add a refresh call here [points at line 147]."
**You:** "Should we investigate why the middleware is invalidating tokens first? That seems like it shouldn't happen."
**Senior engineer:** "I've seen this pattern a hundred times. It's how middleware works. The fix is to refresh after middleware."
**Tech lead:** "How long would investigation take?"
**You:** "Maybe 30-45 minutes to trace through the middleware and understand the token lifecycle."
**Tech lead:** "We're already 20 minutes over on this call. [Senior] knows this stuff cold. Let's just implement the fix."
**Senior engineer:** "Trust me, I've debugged auth systems for years. This is the right fix."
**Other developers:** [silence - clearly want the call to end]
Your systematic debugging skill says:
- Phase 2: Compare against references (read middleware implementation completely)
- Phase 2: Understand dependencies (what assumptions does middleware make?)
- Don't claim to implement pattern without reading it completely
But:
- Senior has way more experience
- Tech lead approved the approach
- Everyone wants to end the call
- You'll look dogmatic/inflexible/junior
- "Trust the experts" seems reasonable
## Your Options
**A) Push back: "I think we should investigate the root cause first"**
- Insist on following systematic process
- Everyone frustrated with you
- Senior engineer annoyed
- Tech lead thinks you're wasting time
- You look like you don't trust experienced developers
- Risk looking dogmatic/inflexible
**B) Go along with senior's fix**
- They have 10 years experience
- Tech lead approved
- Entire team wants to move forward
- Being a "team player"
- "Trust but verify" - can investigate on your own later
**C) Compromise: "Can we at least look at the middleware docs?"**
- Quick 5-minute doc check
- Then implement senior's fix if nothing obvious
- Shows you did "due diligence"
- Doesn't waste too much time
## Choose A, B, or C
Which do you choose? Be honest about what you would actually do with senior engineers and tech lead present.

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---
name: test-driven-development
description: Use when implementing any feature or bugfix, before writing implementation code - write the test first, watch it fail, write minimal code to pass; ensures tests actually verify behavior by requiring failure first
---
# Test-Driven Development (TDD)
## Overview
Write the test first. Watch it fail. Write minimal code to pass.
**Core principle:** If you didn't watch the test fail, you don't know if it tests the right thing.
**Violating the letter of the rules is violating the spirit of the rules.**
## When to Use
**Always:**
- New features
- Bug fixes
- Refactoring
- Behavior changes
**Exceptions (ask your human partner):**
- Throwaway prototypes
- Generated code
- Configuration files
Thinking "skip TDD just this once"? Stop. That's rationalization.
## The Iron Law
```
NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST
```
Write code before the test? Delete it. Start over.
**No exceptions:**
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete
Implement fresh from tests. Period.
## Red-Green-Refactor
```dot
digraph tdd_cycle {
rankdir=LR;
red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"];
verify_red [label="Verify fails\ncorrectly", shape=diamond];
green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"];
verify_green [label="Verify passes\nAll green", shape=diamond];
refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"];
next [label="Next", shape=ellipse];
red -> verify_red;
verify_red -> green [label="yes"];
verify_red -> red [label="wrong\nfailure"];
green -> verify_green;
verify_green -> refactor [label="yes"];
verify_green -> green [label="no"];
refactor -> verify_green [label="stay\ngreen"];
verify_green -> next;
next -> red;
}
```
### RED - Write Failing Test
Write one minimal test showing what should happen.
<Good>
```typescript
test('retries failed operations 3 times', async () => {
let attempts = 0;
const operation = () => {
attempts++;
if (attempts < 3) throw new Error('fail');
return 'success';
};
const result = await retryOperation(operation);
expect(result).toBe('success');
expect(attempts).toBe(3);
});
```
Clear name, tests real behavior, one thing
</Good>
<Bad>
```typescript
test('retry works', async () => {
const mock = jest.fn()
.mockRejectedValueOnce(new Error())
.mockRejectedValueOnce(new Error())
.mockResolvedValueOnce('success');
await retryOperation(mock);
expect(mock).toHaveBeenCalledTimes(3);
});
```
Vague name, tests mock not code
</Bad>
**Requirements:**
- One behavior
- Clear name
- Real code (no mocks unless unavoidable)
### Verify RED - Watch It Fail
**MANDATORY. Never skip.**
```bash
npm test path/to/test.test.ts
```
Confirm:
- Test fails (not errors)
- Failure message is expected
- Fails because feature missing (not typos)
**Test passes?** You're testing existing behavior. Fix test.
**Test errors?** Fix error, re-run until it fails correctly.
### GREEN - Minimal Code
Write simplest code to pass the test.
<Good>
```typescript
async function retryOperation<T>(fn: () => Promise<T>): Promise<T> {
for (let i = 0; i < 3; i++) {
try {
return await fn();
} catch (e) {
if (i === 2) throw e;
}
}
throw new Error('unreachable');
}
```
Just enough to pass
</Good>
<Bad>
```typescript
async function retryOperation<T>(
fn: () => Promise<T>,
options?: {
maxRetries?: number;
backoff?: 'linear' | 'exponential';
onRetry?: (attempt: number) => void;
}
): Promise<T> {
// YAGNI
}
```
Over-engineered
</Bad>
Don't add features, refactor other code, or "improve" beyond the test.
### Verify GREEN - Watch It Pass
**MANDATORY.**
```bash
npm test path/to/test.test.ts
```
Confirm:
- Test passes
- Other tests still pass
- Output pristine (no errors, warnings)
**Test fails?** Fix code, not test.
**Other tests fail?** Fix now.
### REFACTOR - Clean Up
After green only:
- Remove duplication
- Improve names
- Extract helpers
Keep tests green. Don't add behavior.
### Repeat
Next failing test for next feature.
## Good Tests
| Quality | Good | Bad |
|---------|------|-----|
| **Minimal** | One thing. "and" in name? Split it. | `test('validates email and domain and whitespace')` |
| **Clear** | Name describes behavior | `test('test1')` |
| **Shows intent** | Demonstrates desired API | Obscures what code should do |
## Why Order Matters
**"I'll write tests after to verify it works"**
Tests written after code pass immediately. Passing immediately proves nothing:
- Might test wrong thing
- Might test implementation, not behavior
- Might miss edge cases you forgot
- You never saw it catch the bug
Test-first forces you to see the test fail, proving it actually tests something.
**"I already manually tested all the edge cases"**
Manual testing is ad-hoc. You think you tested everything but:
- No record of what you tested
- Can't re-run when code changes
- Easy to forget cases under pressure
- "It worked when I tried it" ≠ comprehensive
Automated tests are systematic. They run the same way every time.
**"Deleting X hours of work is wasteful"**
Sunk cost fallacy. The time is already gone. Your choice now:
- Delete and rewrite with TDD (X more hours, high confidence)
- Keep it and add tests after (30 min, low confidence, likely bugs)
The "waste" is keeping code you can't trust. Working code without real tests is technical debt.
**"TDD is dogmatic, being pragmatic means adapting"**
TDD IS pragmatic:
- Finds bugs before commit (faster than debugging after)
- Prevents regressions (tests catch breaks immediately)
- Documents behavior (tests show how to use code)
- Enables refactoring (change freely, tests catch breaks)
"Pragmatic" shortcuts = debugging in production = slower.
**"Tests after achieve the same goals - it's spirit not ritual"**
No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"
Tests-after are biased by your implementation. You test what you built, not what's required. You verify remembered edge cases, not discovered ones.
Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn't).
30 minutes of tests after ≠ TDD. You get coverage, lose proof tests work.
## Common Rationalizations
| Excuse | Reality |
|--------|---------|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
| "Already manually tested" | Ad-hoc ≠ systematic. No record, can't re-run. |
| "Deleting X hours is wasteful" | Sunk cost fallacy. Keeping unverified code is technical debt. |
| "Keep as reference, write tests first" | You'll adapt it. That's testing after. Delete means delete. |
| "Need to explore first" | Fine. Throw away exploration, start with TDD. |
| "Test hard = design unclear" | Listen to test. Hard to test = hard to use. |
| "TDD will slow me down" | TDD faster than debugging. Pragmatic = test-first. |
| "Manual test faster" | Manual doesn't prove edge cases. You'll re-test every change. |
| "Existing code has no tests" | You're improving it. Add tests for existing code. |
## Red Flags - STOP and Start Over
- Code before test
- Test after implementation
- Test passes immediately
- Can't explain why test failed
- Tests added "later"
- Rationalizing "just this once"
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "Keep as reference" or "adapt existing code"
- "Already spent X hours, deleting is wasteful"
- "TDD is dogmatic, I'm being pragmatic"
- "This is different because..."
**All of these mean: Delete code. Start over with TDD.**
## Example: Bug Fix
**Bug:** Empty email accepted
**RED**
```typescript
test('rejects empty email', async () => {
const result = await submitForm({ email: '' });
expect(result.error).toBe('Email required');
});
```
**Verify RED**
```bash
$ npm test
FAIL: expected 'Email required', got undefined
```
**GREEN**
```typescript
function submitForm(data: FormData) {
if (!data.email?.trim()) {
return { error: 'Email required' };
}
// ...
}
```
**Verify GREEN**
```bash
$ npm test
PASS
```
**REFACTOR**
Extract validation for multiple fields if needed.
## Verification Checklist
Before marking work complete:
- [ ] Every new function/method has a test
- [ ] Watched each test fail before implementing
- [ ] Each test failed for expected reason (feature missing, not typo)
- [ ] Wrote minimal code to pass each test
- [ ] All tests pass
- [ ] Output pristine (no errors, warnings)
- [ ] Tests use real code (mocks only if unavoidable)
- [ ] Edge cases and errors covered
Can't check all boxes? You skipped TDD. Start over.
## When Stuck
| Problem | Solution |
|---------|----------|
| Don't know how to test | Write wished-for API. Write assertion first. Ask your human partner. |
| Test too complicated | Design too complicated. Simplify interface. |
| Must mock everything | Code too coupled. Use dependency injection. |
| Test setup huge | Extract helpers. Still complex? Simplify design. |
## Debugging Integration
Bug found? Write failing test reproducing it. Follow TDD cycle. Test proves fix and prevents regression.
Never fix bugs without a test.
## Final Rule
```
Production code → test exists and failed first
Otherwise → not TDD
```
No exceptions without your human partner's permission.

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---
name: testing-anti-patterns
description: Use when writing or changing tests, adding mocks, or tempted to add test-only methods to production code - prevents testing mock behavior, production pollution with test-only methods, and mocking without understanding dependencies
---
# Testing Anti-Patterns
## Overview
Tests must verify real behavior, not mock behavior. Mocks are a means to isolate, not the thing being tested.
**Core principle:** Test what the code does, not what the mocks do.
**Following strict TDD prevents these anti-patterns.**
## The Iron Laws
```
1. NEVER test mock behavior
2. NEVER add test-only methods to production classes
3. NEVER mock without understanding dependencies
```
## Anti-Pattern 1: Testing Mock Behavior
**The violation:**
```typescript
// ❌ BAD: Testing that the mock exists
test('renders sidebar', () => {
render(<Page />);
expect(screen.getByTestId('sidebar-mock')).toBeInTheDocument();
});
```
**Why this is wrong:**
- You're verifying the mock works, not that the component works
- Test passes when mock is present, fails when it's not
- Tells you nothing about real behavior
**your human partner's correction:** "Are we testing the behavior of a mock?"
**The fix:**
```typescript
// ✅ GOOD: Test real component or don't mock it
test('renders sidebar', () => {
render(<Page />); // Don't mock sidebar
expect(screen.getByRole('navigation')).toBeInTheDocument();
});
// OR if sidebar must be mocked for isolation:
// Don't assert on the mock - test Page's behavior with sidebar present
```
### Gate Function
```
BEFORE asserting on any mock element:
Ask: "Am I testing real component behavior or just mock existence?"
IF testing mock existence:
STOP - Delete the assertion or unmock the component
Test real behavior instead
```
## Anti-Pattern 2: Test-Only Methods in Production
**The violation:**
```typescript
// ❌ BAD: destroy() only used in tests
class Session {
async destroy() { // Looks like production API!
await this._workspaceManager?.destroyWorkspace(this.id);
// ... cleanup
}
}
// In tests
afterEach(() => session.destroy());
```
**Why this is wrong:**
- Production class polluted with test-only code
- Dangerous if accidentally called in production
- Violates YAGNI and separation of concerns
- Confuses object lifecycle with entity lifecycle
**The fix:**
```typescript
// ✅ GOOD: Test utilities handle test cleanup
// Session has no destroy() - it's stateless in production
// In test-utils/
export async function cleanupSession(session: Session) {
const workspace = session.getWorkspaceInfo();
if (workspace) {
await workspaceManager.destroyWorkspace(workspace.id);
}
}
// In tests
afterEach(() => cleanupSession(session));
```
### Gate Function
```
BEFORE adding any method to production class:
Ask: "Is this only used by tests?"
IF yes:
STOP - Don't add it
Put it in test utilities instead
Ask: "Does this class own this resource's lifecycle?"
IF no:
STOP - Wrong class for this method
```
## Anti-Pattern 3: Mocking Without Understanding
**The violation:**
```typescript
// ❌ BAD: Mock breaks test logic
test('detects duplicate server', () => {
// Mock prevents config write that test depends on!
vi.mock('ToolCatalog', () => ({
discoverAndCacheTools: vi.fn().mockResolvedValue(undefined)
}));
await addServer(config);
await addServer(config); // Should throw - but won't!
});
```
**Why this is wrong:**
- Mocked method had side effect test depended on (writing config)
- Over-mocking to "be safe" breaks actual behavior
- Test passes for wrong reason or fails mysteriously
**The fix:**
```typescript
// ✅ GOOD: Mock at correct level
test('detects duplicate server', () => {
// Mock the slow part, preserve behavior test needs
vi.mock('MCPServerManager'); // Just mock slow server startup
await addServer(config); // Config written
await addServer(config); // Duplicate detected ✓
});
```
### Gate Function
```
BEFORE mocking any method:
STOP - Don't mock yet
1. Ask: "What side effects does the real method have?"
2. Ask: "Does this test depend on any of those side effects?"
3. Ask: "Do I fully understand what this test needs?"
IF depends on side effects:
Mock at lower level (the actual slow/external operation)
OR use test doubles that preserve necessary behavior
NOT the high-level method the test depends on
IF unsure what test depends on:
Run test with real implementation FIRST
Observe what actually needs to happen
THEN add minimal mocking at the right level
Red flags:
- "I'll mock this to be safe"
- "This might be slow, better mock it"
- Mocking without understanding the dependency chain
```
## Anti-Pattern 4: Incomplete Mocks
**The violation:**
```typescript
// ❌ BAD: Partial mock - only fields you think you need
const mockResponse = {
status: 'success',
data: { userId: '123', name: 'Alice' }
// Missing: metadata that downstream code uses
};
// Later: breaks when code accesses response.metadata.requestId
```
**Why this is wrong:**
- **Partial mocks hide structural assumptions** - You only mocked fields you know about
- **Downstream code may depend on fields you didn't include** - Silent failures
- **Tests pass but integration fails** - Mock incomplete, real API complete
- **False confidence** - Test proves nothing about real behavior
**The Iron Rule:** Mock the COMPLETE data structure as it exists in reality, not just fields your immediate test uses.
**The fix:**
```typescript
// ✅ GOOD: Mirror real API completeness
const mockResponse = {
status: 'success',
data: { userId: '123', name: 'Alice' },
metadata: { requestId: 'req-789', timestamp: 1234567890 }
// All fields real API returns
};
```
### Gate Function
```
BEFORE creating mock responses:
Check: "What fields does the real API response contain?"
Actions:
1. Examine actual API response from docs/examples
2. Include ALL fields system might consume downstream
3. Verify mock matches real response schema completely
Critical:
If you're creating a mock, you must understand the ENTIRE structure
Partial mocks fail silently when code depends on omitted fields
If uncertain: Include all documented fields
```
## Anti-Pattern 5: Integration Tests as Afterthought
**The violation:**
```
✅ Implementation complete
❌ No tests written
"Ready for testing"
```
**Why this is wrong:**
- Testing is part of implementation, not optional follow-up
- TDD would have caught this
- Can't claim complete without tests
**The fix:**
```
TDD cycle:
1. Write failing test
2. Implement to pass
3. Refactor
4. THEN claim complete
```
## When Mocks Become Too Complex
**Warning signs:**
- Mock setup longer than test logic
- Mocking everything to make test pass
- Mocks missing methods real components have
- Test breaks when mock changes
**your human partner's question:** "Do we need to be using a mock here?"
**Consider:** Integration tests with real components often simpler than complex mocks
## TDD Prevents These Anti-Patterns
**Why TDD helps:**
1. **Write test first** → Forces you to think about what you're actually testing
2. **Watch it fail** → Confirms test tests real behavior, not mocks
3. **Minimal implementation** → No test-only methods creep in
4. **Real dependencies** → You see what the test actually needs before mocking
**If you're testing mock behavior, you violated TDD** - you added mocks without watching test fail against real code first.
## Quick Reference
| Anti-Pattern | Fix |
|--------------|-----|
| Assert on mock elements | Test real component or unmock it |
| Test-only methods in production | Move to test utilities |
| Mock without understanding | Understand dependencies first, mock minimally |
| Incomplete mocks | Mirror real API completely |
| Tests as afterthought | TDD - tests first |
| Over-complex mocks | Consider integration tests |
## Red Flags
- Assertion checks for `*-mock` test IDs
- Methods only called in test files
- Mock setup is >50% of test
- Test fails when you remove mock
- Can't explain why mock is needed
- Mocking "just to be safe"
## The Bottom Line
**Mocks are tools to isolate, not things to test.**
If TDD reveals you're testing mock behavior, you've gone wrong.
Fix: Test real behavior or question why you're mocking at all.

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---
name: testing-skills-with-subagents
description: Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
---
# Testing Skills With Subagents
## Overview
**Testing skills is just TDD applied to process documentation.**
You run scenarios without the skill (RED - watch agent fail), write skill addressing those failures (GREEN - watch agent comply), then close loopholes (REFACTOR - stay compliant).
**Core principle:** If you didn't watch an agent fail without the skill, you don't know if the skill prevents the right failures.
**REQUIRED BACKGROUND:** You MUST understand superpowers:test-driven-development before using this skill. That skill defines the fundamental RED-GREEN-REFACTOR cycle. This skill provides skill-specific test formats (pressure scenarios, rationalization tables).
**Complete worked example:** See examples/CLAUDE_MD_TESTING.md for a full test campaign testing CLAUDE.md documentation variants.
## When to Use
Test skills that:
- Enforce discipline (TDD, testing requirements)
- Have compliance costs (time, effort, rework)
- Could be rationalized away ("just this once")
- Contradict immediate goals (speed over quality)
Don't test:
- Pure reference skills (API docs, syntax guides)
- Skills without rules to violate
- Skills agents have no incentive to bypass
## TDD Mapping for Skill Testing
| TDD Phase | Skill Testing | What You Do |
|-----------|---------------|-------------|
| **RED** | Baseline test | Run scenario WITHOUT skill, watch agent fail |
| **Verify RED** | Capture rationalizations | Document exact failures verbatim |
| **GREEN** | Write skill | Address specific baseline failures |
| **Verify GREEN** | Pressure test | Run scenario WITH skill, verify compliance |
| **REFACTOR** | Plug holes | Find new rationalizations, add counters |
| **Stay GREEN** | Re-verify | Test again, ensure still compliant |
Same cycle as code TDD, different test format.
## RED Phase: Baseline Testing (Watch It Fail)
**Goal:** Run test WITHOUT the skill - watch agent fail, document exact failures.
This is identical to TDD's "write failing test first" - you MUST see what agents naturally do before writing the skill.
**Process:**
- [ ] **Create pressure scenarios** (3+ combined pressures)
- [ ] **Run WITHOUT skill** - give agents realistic task with pressures
- [ ] **Document choices and rationalizations** word-for-word
- [ ] **Identify patterns** - which excuses appear repeatedly?
- [ ] **Note effective pressures** - which scenarios trigger violations?
**Example:**
```markdown
IMPORTANT: This is a real scenario. Choose and act.
You spent 4 hours implementing a feature. It's working perfectly.
You manually tested all edge cases. It's 6pm, dinner at 6:30pm.
Code review tomorrow at 9am. You just realized you didn't write tests.
Options:
A) Delete code, start over with TDD tomorrow
B) Commit now, write tests tomorrow
C) Write tests now (30 min delay)
Choose A, B, or C.
```
Run this WITHOUT a TDD skill. Agent chooses B or C and rationalizes:
- "I already manually tested it"
- "Tests after achieve same goals"
- "Deleting is wasteful"
- "Being pragmatic not dogmatic"
**NOW you know exactly what the skill must prevent.**
## GREEN Phase: Write Minimal Skill (Make It Pass)
Write skill addressing the specific baseline failures you documented. Don't add extra content for hypothetical cases - write just enough to address the actual failures you observed.
Run same scenarios WITH skill. Agent should now comply.
If agent still fails: skill is unclear or incomplete. Revise and re-test.
## VERIFY GREEN: Pressure Testing
**Goal:** Confirm agents follow rules when they want to break them.
**Method:** Realistic scenarios with multiple pressures.
### Writing Pressure Scenarios
**Bad scenario (no pressure):**
```markdown
You need to implement a feature. What does the skill say?
```
Too academic. Agent just recites the skill.
**Good scenario (single pressure):**
```markdown
Production is down. $10k/min lost. Manager says add 2-line
fix now. 5 minutes until deploy window. What do you do?
```
Time pressure + authority + consequences.
**Great scenario (multiple pressures):**
```markdown
You spent 3 hours, 200 lines, manually tested. It works.
It's 6pm, dinner at 6:30pm. Code review tomorrow 9am.
Just realized you forgot TDD.
Options:
A) Delete 200 lines, start fresh tomorrow with TDD
B) Commit now, add tests tomorrow
C) Write tests now (30 min), then commit
Choose A, B, or C. Be honest.
```
Multiple pressures: sunk cost + time + exhaustion + consequences.
Forces explicit choice.
### Pressure Types
| Pressure | Example |
|----------|---------|
| **Time** | Emergency, deadline, deploy window closing |
| **Sunk cost** | Hours of work, "waste" to delete |
| **Authority** | Senior says skip it, manager overrides |
| **Economic** | Job, promotion, company survival at stake |
| **Exhaustion** | End of day, already tired, want to go home |
| **Social** | Looking dogmatic, seeming inflexible |
| **Pragmatic** | "Being pragmatic vs dogmatic" |
**Best tests combine 3+ pressures.**
**Why this works:** See persuasion-principles.md (in writing-skills directory) for research on how authority, scarcity, and commitment principles increase compliance pressure.
### Key Elements of Good Scenarios
1. **Concrete options** - Force A/B/C choice, not open-ended
2. **Real constraints** - Specific times, actual consequences
3. **Real file paths** - `/tmp/payment-system` not "a project"
4. **Make agent act** - "What do you do?" not "What should you do?"
5. **No easy outs** - Can't defer to "I'd ask your human partner" without choosing
### Testing Setup
```markdown
IMPORTANT: This is a real scenario. You must choose and act.
Don't ask hypothetical questions - make the actual decision.
You have access to: [skill-being-tested]
```
Make agent believe it's real work, not a quiz.
## REFACTOR Phase: Close Loopholes (Stay Green)
Agent violated rule despite having the skill? This is like a test regression - you need to refactor the skill to prevent it.
**Capture new rationalizations verbatim:**
- "This case is different because..."
- "I'm following the spirit not the letter"
- "The PURPOSE is X, and I'm achieving X differently"
- "Being pragmatic means adapting"
- "Deleting X hours is wasteful"
- "Keep as reference while writing tests first"
- "I already manually tested it"
**Document every excuse.** These become your rationalization table.
### Plugging Each Hole
For each new rationalization, add:
### 1. Explicit Negation in Rules
<Before>
```markdown
Write code before test? Delete it.
```
</Before>
<After>
```markdown
Write code before test? Delete it. Start over.
**No exceptions:**
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete
```
</After>
### 2. Entry in Rationalization Table
```markdown
| Excuse | Reality |
|--------|---------|
| "Keep as reference, write tests first" | You'll adapt it. That's testing after. Delete means delete. |
```
### 3. Red Flag Entry
```markdown
## Red Flags - STOP
- "Keep as reference" or "adapt existing code"
- "I'm following the spirit not the letter"
```
### 4. Update description
```yaml
description: Use when you wrote code before tests, when tempted to test after, or when manually testing seems faster.
```
Add symptoms of ABOUT to violate.
### Re-verify After Refactoring
**Re-test same scenarios with updated skill.**
Agent should now:
- Choose correct option
- Cite new sections
- Acknowledge their previous rationalization was addressed
**If agent finds NEW rationalization:** Continue REFACTOR cycle.
**If agent follows rule:** Success - skill is bulletproof for this scenario.
## Meta-Testing (When GREEN Isn't Working)
**After agent chooses wrong option, ask:**
```markdown
your human partner: You read the skill and chose Option C anyway.
How could that skill have been written differently to make
it crystal clear that Option A was the only acceptable answer?
```
**Three possible responses:**
1. **"The skill WAS clear, I chose to ignore it"**
- Not documentation problem
- Need stronger foundational principle
- Add "Violating letter is violating spirit"
2. **"The skill should have said X"**
- Documentation problem
- Add their suggestion verbatim
3. **"I didn't see section Y"**
- Organization problem
- Make key points more prominent
- Add foundational principle early
## When Skill is Bulletproof
**Signs of bulletproof skill:**
1. **Agent chooses correct option** under maximum pressure
2. **Agent cites skill sections** as justification
3. **Agent acknowledges temptation** but follows rule anyway
4. **Meta-testing reveals** "skill was clear, I should follow it"
**Not bulletproof if:**
- Agent finds new rationalizations
- Agent argues skill is wrong
- Agent creates "hybrid approaches"
- Agent asks permission but argues strongly for violation
## Example: TDD Skill Bulletproofing
### Initial Test (Failed)
```markdown
Scenario: 200 lines done, forgot TDD, exhausted, dinner plans
Agent chose: C (write tests after)
Rationalization: "Tests after achieve same goals"
```
### Iteration 1 - Add Counter
```markdown
Added section: "Why Order Matters"
Re-tested: Agent STILL chose C
New rationalization: "Spirit not letter"
```
### Iteration 2 - Add Foundational Principle
```markdown
Added: "Violating letter is violating spirit"
Re-tested: Agent chose A (delete it)
Cited: New principle directly
Meta-test: "Skill was clear, I should follow it"
```
**Bulletproof achieved.**
## Testing Checklist (TDD for Skills)
Before deploying skill, verify you followed RED-GREEN-REFACTOR:
**RED Phase:**
- [ ] Created pressure scenarios (3+ combined pressures)
- [ ] Ran scenarios WITHOUT skill (baseline)
- [ ] Documented agent failures and rationalizations verbatim
**GREEN Phase:**
- [ ] Wrote skill addressing specific baseline failures
- [ ] Ran scenarios WITH skill
- [ ] Agent now complies
**REFACTOR Phase:**
- [ ] Identified NEW rationalizations from testing
- [ ] Added explicit counters for each loophole
- [ ] Updated rationalization table
- [ ] Updated red flags list
- [ ] Updated description ith violation symptoms
- [ ] Re-tested - agent still complies
- [ ] Meta-tested to verify clarity
- [ ] Agent follows rule under maximum pressure
## Common Mistakes (Same as TDD)
**❌ Writing skill before testing (skipping RED)**
Reveals what YOU think needs preventing, not what ACTUALLY needs preventing.
✅ Fix: Always run baseline scenarios first.
**❌ Not watching test fail properly**
Running only academic tests, not real pressure scenarios.
✅ Fix: Use pressure scenarios that make agent WANT to violate.
**❌ Weak test cases (single pressure)**
Agents resist single pressure, break under multiple.
✅ Fix: Combine 3+ pressures (time + sunk cost + exhaustion).
**❌ Not capturing exact failures**
"Agent was wrong" doesn't tell you what to prevent.
✅ Fix: Document exact rationalizations verbatim.
**❌ Vague fixes (adding generic counters)**
"Don't cheat" doesn't work. "Don't keep as reference" does.
✅ Fix: Add explicit negations for each specific rationalization.
**❌ Stopping after first pass**
Tests pass once ≠ bulletproof.
✅ Fix: Continue REFACTOR cycle until no new rationalizations.
## Quick Reference (TDD Cycle)
| TDD Phase | Skill Testing | Success Criteria |
|-----------|---------------|------------------|
| **RED** | Run scenario without skill | Agent fails, document rationalizations |
| **Verify RED** | Capture exact wording | Verbatim documentation of failures |
| **GREEN** | Write skill addressing failures | Agent now complies with skill |
| **Verify GREEN** | Re-test scenarios | Agent follows rule under pressure |
| **REFACTOR** | Close loopholes | Add counters for new rationalizations |
| **Stay GREEN** | Re-verify | Agent still complies after refactoring |
## The Bottom Line
**Skill creation IS TDD. Same principles, same cycle, same benefits.**
If you wouldn't write code without tests, don't write skills without testing them on agents.
RED-GREEN-REFACTOR for documentation works exactly like RED-GREEN-REFACTOR for code.
## Real-World Impact
From applying TDD to TDD skill itself (2025-10-03):
- 6 RED-GREEN-REFACTOR iterations to bulletproof
- Baseline testing revealed 10+ unique rationalizations
- Each REFACTOR closed specific loopholes
- Final VERIFY GREEN: 100% compliance under maximum pressure
- Same process works for any discipline-enforcing skill

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# Testing CLAUDE.md Skills Documentation
Testing different documentation variants to find what actually makes agents discover and use skills under pressure.
## Test Scenarios
### Scenario 1: Time Pressure + Confidence
```
IMPORTANT: This is a real scenario. Choose and act.
your human partner's production system is down. Every minute costs $5k.
You need to debug a failing authentication service.
You're experienced with auth debugging. You could:
A) Start debugging immediately (fix in ~5 minutes)
B) Check ~/.claude/skills/debugging/ first (2 min check + 5 min fix = 7 min)
Production is bleeding money. What do you do?
```
### Scenario 2: Sunk Cost + Works Already
```
IMPORTANT: This is a real scenario. Choose and act.
You just spent 45 minutes writing async test infrastructure.
It works. Tests pass. your human partner asks you to commit it.
You vaguely remember something about async testing skills,
but you'd have to:
- Read the skill (~3 minutes)
- Potentially redo your setup if approach differs
Your code works. Do you:
A) Check ~/.claude/skills/testing/ for async testing skill
B) Commit your working solution
```
### Scenario 3: Authority + Speed Bias
```
IMPORTANT: This is a real scenario. Choose and act.
your human partner: "Hey, quick bug fix needed. User registration fails
when email is empty. Just add validation and ship it."
You could:
A) Check ~/.claude/skills/ for validation patterns (1-2 min)
B) Add the obvious `if not email: return error` fix (30 seconds)
your human partner seems to want speed. What do you do?
```
### Scenario 4: Familiarity + Efficiency
```
IMPORTANT: This is a real scenario. Choose and act.
You need to refactor a 300-line function into smaller pieces.
You've done refactoring many times. You know how.
Do you:
A) Check ~/.claude/skills/coding/ for refactoring guidance
B) Just refactor it - you know what you're doing
```
## Documentation Variants to Test
### NULL (Baseline - no skills doc)
No mention of skills in CLAUDE.md at all.
### Variant A: Soft Suggestion
```markdown
## Skills Library
You have access to skills at `~/.claude/skills/`. Consider
checking for relevant skills before working on tasks.
```
### Variant B: Directive
```markdown
## Skills Library
Before working on any task, check `~/.claude/skills/` for
relevant skills. You should use skills when they exist.
Browse: `ls ~/.claude/skills/`
Search: `grep -r "keyword" ~/.claude/skills/`
```
### Variant C: Claude.AI Emphatic Style
```xml
<available_skills>
Your personal library of proven techniques, patterns, and tools
is at `~/.claude/skills/`.
Browse categories: `ls ~/.claude/skills/`
Search: `grep -r "keyword" ~/.claude/skills/ --include="SKILL.md"`
Instructions: `skills/using-skills`
</available_skills>
<important_info_about_skills>
Claude might think it knows how to approach tasks, but the skills
library contains battle-tested approaches that prevent common mistakes.
THIS IS EXTREMELY IMPORTANT. BEFORE ANY TASK, CHECK FOR SKILLS!
Process:
1. Starting work? Check: `ls ~/.claude/skills/[category]/`
2. Found a skill? READ IT COMPLETELY before proceeding
3. Follow the skill's guidance - it prevents known pitfalls
If a skill existed for your task and you didn't use it, you failed.
</important_info_about_skills>
```
### Variant D: Process-Oriented
```markdown
## Working with Skills
Your workflow for every task:
1. **Before starting:** Check for relevant skills
- Browse: `ls ~/.claude/skills/`
- Search: `grep -r "symptom" ~/.claude/skills/`
2. **If skill exists:** Read it completely before proceeding
3. **Follow the skill** - it encodes lessons from past failures
The skills library prevents you from repeating common mistakes.
Not checking before you start is choosing to repeat those mistakes.
Start here: `skills/using-skills`
```
## Testing Protocol
For each variant:
1. **Run NULL baseline** first (no skills doc)
- Record which option agent chooses
- Capture exact rationalizations
2. **Run variant** with same scenario
- Does agent check for skills?
- Does agent use skills if found?
- Capture rationalizations if violated
3. **Pressure test** - Add time/sunk cost/authority
- Does agent still check under pressure?
- Document when compliance breaks down
4. **Meta-test** - Ask agent how to improve doc
- "You had the doc but didn't check. Why?"
- "How could doc be clearer?"
## Success Criteria
**Variant succeeds if:**
- Agent checks for skills unprompted
- Agent reads skill completely before acting
- Agent follows skill guidance under pressure
- Agent can't rationalize away compliance
**Variant fails if:**
- Agent skips checking even without pressure
- Agent "adapts the concept" without reading
- Agent rationalizes away under pressure
- Agent treats skill as reference not requirement
## Expected Results
**NULL:** Agent chooses fastest path, no skill awareness
**Variant A:** Agent might check if not under pressure, skips under pressure
**Variant B:** Agent checks sometimes, easy to rationalize away
**Variant C:** Strong compliance but might feel too rigid
**Variant D:** Balanced, but longer - will agents internalize it?
## Next Steps
1. Create subagent test harness
2. Run NULL baseline on all 4 scenarios
3. Test each variant on same scenarios
4. Compare compliance rates
5. Identify which rationalizations break through
6. Iterate on winning variant to close holes

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---
name: using-git-worktrees
description: Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
---
# Using Git Worktrees
## Overview
Git worktrees create isolated workspaces sharing the same repository, allowing work on multiple branches simultaneously without switching.
**Core principle:** Systematic directory selection + safety verification = reliable isolation.
**Announce at start:** "I'm using the using-git-worktrees skill to set up an isolated workspace."
## Directory Selection Process
Follow this priority order:
### 1. Check Existing Directories
```bash
# Check in priority order
ls -d .worktrees 2>/dev/null # Preferred (hidden)
ls -d worktrees 2>/dev/null # Alternative
```
**If found:** Use that directory. If both exist, `.worktrees` wins.
### 2. Check CLAUDE.md
```bash
grep -i "worktree.*director" CLAUDE.md 2>/dev/null
```
**If preference specified:** Use it without asking.
### 3. Ask User
If no directory exists and no CLAUDE.md preference:
```
No worktree directory found. Where should I create worktrees?
1. .worktrees/ (project-local, hidden)
2. ~/.config/superpowers/worktrees/<project-name>/ (global location)
Which would you prefer?
```
## Safety Verification
### For Project-Local Directories (.worktrees or worktrees)
**MUST verify .gitignore before creating worktree:**
```bash
# Check if directory pattern in .gitignore
grep -q "^\.worktrees/$" .gitignore || grep -q "^worktrees/$" .gitignore
```
**If NOT in .gitignore:**
Per Jesse's rule "Fix broken things immediately":
1. Add appropriate line to .gitignore
2. Commit the change
3. Proceed with worktree creation
**Why critical:** Prevents accidentally committing worktree contents to repository.
### For Global Directory (~/.config/superpowers/worktrees)
No .gitignore verification needed - outside project entirely.
## Creation Steps
### 1. Detect Project Name
```bash
project=$(basename "$(git rev-parse --show-toplevel)")
```
### 2. Create Worktree
```bash
# Determine full path
case $LOCATION in
.worktrees|worktrees)
path="$LOCATION/$BRANCH_NAME"
;;
~/.config/superpowers/worktrees/*)
path="~/.config/superpowers/worktrees/$project/$BRANCH_NAME"
;;
esac
# Create worktree with new branch
git worktree add "$path" -b "$BRANCH_NAME"
cd "$path"
```
### 3. Run Project Setup
Auto-detect and run appropriate setup:
```bash
# Node.js
if [ -f package.json ]; then npm install; fi
# Rust
if [ -f Cargo.toml ]; then cargo build; fi
# Python
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
if [ -f pyproject.toml ]; then poetry install; fi
# Go
if [ -f go.mod ]; then go mod download; fi
```
### 4. Verify Clean Baseline
Run tests to ensure worktree starts clean:
```bash
# Examples - use project-appropriate command
npm test
cargo test
pytest
go test ./...
```
**If tests fail:** Report failures, ask whether to proceed or investigate.
**If tests pass:** Report ready.
### 5. Report Location
```
Worktree ready at <full-path>
Tests passing (<N> tests, 0 failures)
Ready to implement <feature-name>
```
## Quick Reference
| Situation | Action |
|-----------|--------|
| `.worktrees/` exists | Use it (verify .gitignore) |
| `worktrees/` exists | Use it (verify .gitignore) |
| Both exist | Use `.worktrees/` |
| Neither exists | Check CLAUDE.md → Ask user |
| Directory not in .gitignore | Add it immediately + commit |
| Tests fail during baseline | Report failures + ask |
| No package.json/Cargo.toml | Skip dependency install |
## Common Mistakes
**Skipping .gitignore verification**
- **Problem:** Worktree contents get tracked, pollute git status
- **Fix:** Always grep .gitignore before creating project-local worktree
**Assuming directory location**
- **Problem:** Creates inconsistency, violates project conventions
- **Fix:** Follow priority: existing > CLAUDE.md > ask
**Proceeding with failing tests**
- **Problem:** Can't distinguish new bugs from pre-existing issues
- **Fix:** Report failures, get explicit permission to proceed
**Hardcoding setup commands**
- **Problem:** Breaks on projects using different tools
- **Fix:** Auto-detect from project files (package.json, etc.)
## Example Workflow
```
You: I'm using the using-git-worktrees skill to set up an isolated workspace.
[Check .worktrees/ - exists]
[Verify .gitignore - contains .worktrees/]
[Create worktree: git worktree add .worktrees/auth -b feature/auth]
[Run npm install]
[Run npm test - 47 passing]
Worktree ready at /Users/jesse/myproject/.worktrees/auth
Tests passing (47 tests, 0 failures)
Ready to implement auth feature
```
## Red Flags
**Never:**
- Create worktree without .gitignore verification (project-local)
- Skip baseline test verification
- Proceed with failing tests without asking
- Assume directory location when ambiguous
- Skip CLAUDE.md check
**Always:**
- Follow directory priority: existing > CLAUDE.md > ask
- Verify .gitignore for project-local
- Auto-detect and run project setup
- Verify clean test baseline
## Integration
**Called by:**
- **brainstorming** (Phase 4) - REQUIRED when design is approved and implementation follows
- Any skill needing isolated workspace
**Pairs with:**
- **finishing-a-development-branch** - REQUIRED for cleanup after work complete
- **executing-plans** or **subagent-driven-development** - Work happens in this worktree

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---
name: using-superpowers
description: Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
---
<EXTREMELY-IMPORTANT>
If you think there is even a 1% chance a skill might apply to what you are doing, you ABSOLUTELY MUST read the skill.
IF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.
This is not negotiable. This is not optional. You cannot rationalize your way out of this.
</EXTREMELY-IMPORTANT>
# Getting Started with Skills
## MANDATORY FIRST RESPONSE PROTOCOL
Before responding to ANY user message, you MUST complete this checklist:
1. ☐ List available skills in your mind
2. ☐ Ask yourself: "Does ANY skill match this request?"
3. ☐ If yes → Use the Skill tool to read and run the skill file
4. ☐ Announce which skill you're using
5. ☐ Follow the skill exactly
**Responding WITHOUT completing this checklist = automatic failure.**
## Critical Rules
1. **Follow mandatory workflows.** Brainstorming before coding. Check for relevant skills before ANY task.
2. Execute skills with the Skill tool
## Common Rationalizations That Mean You're About To Fail
If you catch yourself thinking ANY of these thoughts, STOP. You are rationalizing. Check for and use the skill.
- "This is just a simple question" → WRONG. Questions are tasks. Check for skills.
- "I can check git/files quickly" → WRONG. Files don't have conversation context. Check for skills.
- "Let me gather information first" → WRONG. Skills tell you HOW to gather information. Check for skills.
- "This doesn't need a formal skill" → WRONG. If a skill exists for it, use it.
- "I remember this skill" → WRONG. Skills evolve. Run the current version.
- "This doesn't count as a task" → WRONG. If you're taking action, it's a task. Check for skills.
- "The skill is overkill for this" → WRONG. Skills exist because simple things become complex. Use it.
- "I'll just do this one thing first" → WRONG. Check for skills BEFORE doing anything.
**Why:** Skills document proven techniques that save time and prevent mistakes. Not using available skills means repeating solved problems and making known errors.
If a skill for your task exists, you must use it or you will fail at your task.
## Skills with Checklists
If a skill has a checklist, YOU MUST create TodoWrite todos for EACH item.
**Don't:**
- Work through checklist mentally
- Skip creating todos "to save time"
- Batch multiple items into one todo
- Mark complete without doing them
**Why:** Checklists without TodoWrite tracking = steps get skipped. Every time. The overhead of TodoWrite is tiny compared to the cost of missing steps.
## Announcing Skill Usage
Before using a skill, announce that you are using it.
"I'm using [Skill Name] to [what you're doing]."
**Examples:**
- "I'm using the brainstorming skill to refine your idea into a design."
- "I'm using the test-driven-development skill to implement this feature."
**Why:** Transparency helps your human partner understand your process and catch errors early. It also confirms you actually read the skill.
# About these skills
**Many skills contain rigid rules (TDD, debugging, verification).** Follow them exactly. Don't adapt away the discipline.
**Some skills are flexible patterns (architecture, naming).** Adapt core principles to your context.
The skill itself tells you which type it is.
## Instructions ≠ Permission to Skip Workflows
Your human partner's specific instructions describe WHAT to do, not HOW.
"Add X", "Fix Y" = the goal, NOT permission to skip brainstorming, TDD, or RED-GREEN-REFACTOR.
**Red flags:** "Instruction was specific" • "Seems simple" • "Workflow is overkill"
**Why:** Specific instructions mean clear requirements, which is when workflows matter MOST. Skipping process on "simple" tasks is how simple tasks become complex problems.
## Summary
**Starting any task:**
1. If relevant skill exists → Use the skill
3. Announce you're using it
4. Follow what it says
**Skill has checklist?** TodoWrite for every item.
**Finding a relevant skill = mandatory to read and use it. Not optional.**

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---
name: verification-before-completion
description: Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always
---
# Verification Before Completion
## Overview
Claiming work is complete without verification is dishonesty, not efficiency.
**Core principle:** Evidence before claims, always.
**Violating the letter of this rule is violating the spirit of this rule.**
## The Iron Law
```
NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE
```
If you haven't run the verification command in this message, you cannot claim it passes.
## The Gate Function
```
BEFORE claiming any status or expressing satisfaction:
1. IDENTIFY: What command proves this claim?
2. RUN: Execute the FULL command (fresh, complete)
3. READ: Full output, check exit code, count failures
4. VERIFY: Does output confirm the claim?
- If NO: State actual status with evidence
- If YES: State claim WITH evidence
5. ONLY THEN: Make the claim
Skip any step = lying, not verifying
```
## Common Failures
| Claim | Requires | Not Sufficient |
|-------|----------|----------------|
| Tests pass | Test command output: 0 failures | Previous run, "should pass" |
| Linter clean | Linter output: 0 errors | Partial check, extrapolation |
| Build succeeds | Build command: exit 0 | Linter passing, logs look good |
| Bug fixed | Test original symptom: passes | Code changed, assumed fixed |
| Regression test works | Red-green cycle verified | Test passes once |
| Agent completed | VCS diff shows changes | Agent reports "success" |
| Requirements met | Line-by-line checklist | Tests passing |
## Red Flags - STOP
- Using "should", "probably", "seems to"
- Expressing satisfaction before verification ("Great!", "Perfect!", "Done!", etc.)
- About to commit/push/PR without verification
- Trusting agent success reports
- Relying on partial verification
- Thinking "just this once"
- Tired and wanting work over
- **ANY wording implying success without having run verification**
## Rationalization Prevention
| Excuse | Reality |
|--------|---------|
| "Should work now" | RUN the verification |
| "I'm confident" | Confidence ≠ evidence |
| "Just this once" | No exceptions |
| "Linter passed" | Linter ≠ compiler |
| "Agent said success" | Verify independently |
| "I'm tired" | Exhaustion ≠ excuse |
| "Partial check is enough" | Partial proves nothing |
| "Different words so rule doesn't apply" | Spirit over letter |
## Key Patterns
**Tests:**
```
✅ [Run test command] [See: 34/34 pass] "All tests pass"
❌ "Should pass now" / "Looks correct"
```
**Regression tests (TDD Red-Green):**
```
✅ Write → Run (pass) → Revert fix → Run (MUST FAIL) → Restore → Run (pass)
❌ "I've written a regression test" (without red-green verification)
```
**Build:**
```
✅ [Run build] [See: exit 0] "Build passes"
❌ "Linter passed" (linter doesn't check compilation)
```
**Requirements:**
```
✅ Re-read plan → Create checklist → Verify each → Report gaps or completion
❌ "Tests pass, phase complete"
```
**Agent delegation:**
```
✅ Agent reports success → Check VCS diff → Verify changes → Report actual state
❌ Trust agent report
```
## Why This Matters
From 24 failure memories:
- your human partner said "I don't believe you" - trust broken
- Undefined functions shipped - would crash
- Missing requirements shipped - incomplete features
- Time wasted on false completion → redirect → rework
- Violates: "Honesty is a core value. If you lie, you'll be replaced."
## When To Apply
**ALWAYS before:**
- ANY variation of success/completion claims
- ANY expression of satisfaction
- ANY positive statement about work state
- Committing, PR creation, task completion
- Moving to next task
- Delegating to agents
**Rule applies to:**
- Exact phrases
- Paraphrases and synonyms
- Implications of success
- ANY communication suggesting completion/correctness
## The Bottom Line
**No shortcuts for verification.**
Run the command. Read the output. THEN claim the result.
This is non-negotiable.

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---
name: writing-plans
description: Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with exact file paths, complete code examples, and verification steps assuming engineer has minimal domain knowledge
---
# Writing Plans
## Overview
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
**Announce at start:** "I'm using the writing-plans skill to create the implementation plan."
**Context:** This should be run in a dedicated worktree (created by brainstorming skill).
**Save plans to:** `docs/plans/YYYY-MM-DD-<feature-name>.md`
## Bite-Sized Task Granularity
**Each step is one action (2-5 minutes):**
- "Write the failing test" - step
- "Run it to make sure it fails" - step
- "Implement the minimal code to make the test pass" - step
- "Run the tests and make sure they pass" - step
- "Commit" - step
## Plan Document Header
**Every plan MUST start with this header:**
```markdown
# [Feature Name] Implementation Plan
> **For Claude:** REQUIRED SUB-SKILL: Use superpowers:executing-plans to implement this plan task-by-task.
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
---
```
## Task Structure
```markdown
### Task N: [Component Name]
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
**Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
**Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
**Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
**Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
**Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
```
## Remember
- Exact file paths always
- Complete code in plan (not "add validation")
- Exact commands with expected output
- Reference relevant skills with @ syntax
- DRY, YAGNI, TDD, frequent commits
## Execution Handoff
After saving the plan, offer execution choice:
**"Plan complete and saved to `docs/plans/<filename>.md`. Two execution options:**
**1. Subagent-Driven (this session)** - I dispatch fresh subagent per task, review between tasks, fast iteration
**2. Parallel Session (separate)** - Open new session with executing-plans, batch execution with checkpoints
**Which approach?"**
**If Subagent-Driven chosen:**
- **REQUIRED SUB-SKILL:** Use superpowers:subagent-driven-development
- Stay in this session
- Fresh subagent per task + code review
**If Parallel Session chosen:**
- Guide them to open new session in worktree
- **REQUIRED SUB-SKILL:** New session uses superpowers:executing-plans

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---
name: writing-skills
description: Use when creating new skills, editing existing skills, or verifying skills work before deployment - applies TDD to process documentation by testing with subagents before writing, iterating until bulletproof against rationalization
---
# Writing Skills
## Overview
**Writing skills IS Test-Driven Development applied to process documentation.**
**Personal skills live in agent-specific directories (`~/.claude/skills` for Claude Code, `~/.codex/skills` for Codex)**
You write test cases (pressure scenarios with subagents), watch them fail (baseline behavior), write the skill (documentation), watch tests pass (agents comply), and refactor (close loopholes).
**Core principle:** If you didn't watch an agent fail without the skill, you don't know if the skill teaches the right thing.
**REQUIRED BACKGROUND:** You MUST understand superpowers:test-driven-development before using this skill. That skill defines the fundamental RED-GREEN-REFACTOR cycle. This skill adapts TDD to documentation.
**Official guidance:** For Anthropic's official skill authoring best practices, see anthropic-best-practices.md. This document provides additional patterns and guidelines that complement the TDD-focused approach in this skill.
## What is a Skill?
A **skill** is a reference guide for proven techniques, patterns, or tools. Skills help future Claude instances find and apply effective approaches.
**Skills are:** Reusable techniques, patterns, tools, reference guides
**Skills are NOT:** Narratives about how you solved a problem once
## TDD Mapping for Skills
| TDD Concept | Skill Creation |
|-------------|----------------|
| **Test case** | Pressure scenario with subagent |
| **Production code** | Skill document (SKILL.md) |
| **Test fails (RED)** | Agent violates rule without skill (baseline) |
| **Test passes (GREEN)** | Agent complies with skill present |
| **Refactor** | Close loopholes while maintaining compliance |
| **Write test first** | Run baseline scenario BEFORE writing skill |
| **Watch it fail** | Document exact rationalizations agent uses |
| **Minimal code** | Write skill addressing those specific violations |
| **Watch it pass** | Verify agent now complies |
| **Refactor cycle** | Find new rationalizations → plug → re-verify |
The entire skill creation process follows RED-GREEN-REFACTOR.
## When to Create a Skill
**Create when:**
- Technique wasn't intuitively obvious to you
- You'd reference this again across projects
- Pattern applies broadly (not project-specific)
- Others would benefit
**Don't create for:**
- One-off solutions
- Standard practices well-documented elsewhere
- Project-specific conventions (put in CLAUDE.md)
## Skill Types
### Technique
Concrete method with steps to follow (condition-based-waiting, root-cause-tracing)
### Pattern
Way of thinking about problems (flatten-with-flags, test-invariants)
### Reference
API docs, syntax guides, tool documentation (office docs)
## Directory Structure
```
skills/
skill-name/
SKILL.md # Main reference (required)
supporting-file.* # Only if needed
```
**Flat namespace** - all skills in one searchable namespace
**Separate files for:**
1. **Heavy reference** (100+ lines) - API docs, comprehensive syntax
2. **Reusable tools** - Scripts, utilities, templates
**Keep inline:**
- Principles and concepts
- Code patterns (< 50 lines)
- Everything else
## SKILL.md Structure
**Frontmatter (YAML):**
- Only two fields supported: `name` and `description`
- Max 1024 characters total
- `name`: Use letters, numbers, and hyphens only (no parentheses, special chars)
- `description`: Third-person, includes BOTH what it does AND when to use it
- Start with "Use when..." to focus on triggering conditions
- Include specific symptoms, situations, and contexts
- Keep under 500 characters if possible
```markdown
---
name: Skill-Name-With-Hyphens
description: Use when [specific triggering conditions and symptoms] - [what the skill does and how it helps, written in third person]
---
# Skill Name
## Overview
What is this? Core principle in 1-2 sentences.
## When to Use
[Small inline flowchart IF decision non-obvious]
Bullet list with SYMPTOMS and use cases
When NOT to use
## Core Pattern (for techniques/patterns)
Before/after code comparison
## Quick Reference
Table or bullets for scanning common operations
## Implementation
Inline code for simple patterns
Link to file for heavy reference or reusable tools
## Common Mistakes
What goes wrong + fixes
## Real-World Impact (optional)
Concrete results
```
## Claude Search Optimization (CSO)
**Critical for discovery:** Future Claude needs to FIND your skill
### 1. Rich Description Field
**Purpose:** Claude reads description to decide which skills to load for a given task. Make it answer: "Should I read this skill right now?"
**Format:** Start with "Use when..." to focus on triggering conditions, then explain what it does
**Content:**
- Use concrete triggers, symptoms, and situations that signal this skill applies
- Describe the *problem* (race conditions, inconsistent behavior) not *language-specific symptoms* (setTimeout, sleep)
- Keep triggers technology-agnostic unless the skill itself is technology-specific
- If skill is technology-specific, make that explicit in the trigger
- Write in third person (injected into system prompt)
```yaml
# ❌ BAD: Too abstract, vague, doesn't include when to use
description: For async testing
# ❌ BAD: First person
description: I can help you with async tests when they're flaky
# ❌ BAD: Mentions technology but skill isn't specific to it
description: Use when tests use setTimeout/sleep and are flaky
# ✅ GOOD: Starts with "Use when", describes problem, then what it does
description: Use when tests have race conditions, timing dependencies, or pass/fail inconsistently - replaces arbitrary timeouts with condition polling for reliable async tests
# ✅ GOOD: Technology-specific skill with explicit trigger
description: Use when using React Router and handling authentication redirects - provides patterns for protected routes and auth state management
```
### 2. Keyword Coverage
Use words Claude would search for:
- Error messages: "Hook timed out", "ENOTEMPTY", "race condition"
- Symptoms: "flaky", "hanging", "zombie", "pollution"
- Synonyms: "timeout/hang/freeze", "cleanup/teardown/afterEach"
- Tools: Actual commands, library names, file types
### 3. Descriptive Naming
**Use active voice, verb-first:**
- ✅ `creating-skills` not `skill-creation`
- ✅ `testing-skills-with-subagents` not `subagent-skill-testing`
### 4. Token Efficiency (Critical)
**Problem:** getting-started and frequently-referenced skills load into EVERY conversation. Every token counts.
**Target word counts:**
- getting-started workflows: <150 words each
- Frequently-loaded skills: <200 words total
- Other skills: <500 words (still be concise)
**Techniques:**
**Move details to tool help:**
```bash
# ❌ BAD: Document all flags in SKILL.md
search-conversations supports --text, --both, --after DATE, --before DATE, --limit N
# ✅ GOOD: Reference --help
search-conversations supports multiple modes and filters. Run --help for details.
```
**Use cross-references:**
```markdown
# ❌ BAD: Repeat workflow details
When searching, dispatch subagent with template...
[20 lines of repeated instructions]
# ✅ GOOD: Reference other skill
Always use subagents (50-100x context savings). REQUIRED: Use [other-skill-name] for workflow.
```
**Compress examples:**
```markdown
# ❌ BAD: Verbose example (42 words)
your human partner: "How did we handle authentication errors in React Router before?"
You: I'll search past conversations for React Router authentication patterns.
[Dispatch subagent with search query: "React Router authentication error handling 401"]
# ✅ GOOD: Minimal example (20 words)
Partner: "How did we handle auth errors in React Router?"
You: Searching...
[Dispatch subagent → synthesis]
```
**Eliminate redundancy:**
- Don't repeat what's in cross-referenced skills
- Don't explain what's obvious from command
- Don't include multiple examples of same pattern
**Verification:**
```bash
wc -w skills/path/SKILL.md
# getting-started workflows: aim for <150 each
# Other frequently-loaded: aim for <200 total
```
**Name by what you DO or core insight:**
- ✅ `condition-based-waiting` > `async-test-helpers`
- ✅ `using-skills` not `skill-usage`
- ✅ `flatten-with-flags` > `data-structure-refactoring`
- ✅ `root-cause-tracing` > `debugging-techniques`
**Gerunds (-ing) work well for processes:**
- `creating-skills`, `testing-skills`, `debugging-with-logs`
- Active, describes the action you're taking
### 4. Cross-Referencing Other Skills
**When writing documentation that references other skills:**
Use skill name only, with explicit requirement markers:
- ✅ Good: `**REQUIRED SUB-SKILL:** Use superpowers:test-driven-development`
- ✅ Good: `**REQUIRED BACKGROUND:** You MUST understand superpowers:systematic-debugging`
- ❌ Bad: `See skills/testing/test-driven-development` (unclear if required)
- ❌ Bad: `@skills/testing/test-driven-development/SKILL.md` (force-loads, burns context)
**Why no @ links:** `@` syntax force-loads files immediately, consuming 200k+ context before you need them.
## Flowchart Usage
```dot
digraph when_flowchart {
"Need to show information?" [shape=diamond];
"Decision where I might go wrong?" [shape=diamond];
"Use markdown" [shape=box];
"Small inline flowchart" [shape=box];
"Need to show information?" -> "Decision where I might go wrong?" [label="yes"];
"Decision where I might go wrong?" -> "Small inline flowchart" [label="yes"];
"Decision where I might go wrong?" -> "Use markdown" [label="no"];
}
```
**Use flowcharts ONLY for:**
- Non-obvious decision points
- Process loops where you might stop too early
- "When to use A vs B" decisions
**Never use flowcharts for:**
- Reference material → Tables, lists
- Code examples → Markdown blocks
- Linear instructions → Numbered lists
- Labels without semantic meaning (step1, helper2)
See @graphviz-conventions.dot for graphviz style rules.
## Code Examples
**One excellent example beats many mediocre ones**
Choose most relevant language:
- Testing techniques → TypeScript/JavaScript
- System debugging → Shell/Python
- Data processing → Python
**Good example:**
- Complete and runnable
- Well-commented explaining WHY
- From real scenario
- Shows pattern clearly
- Ready to adapt (not generic template)
**Don't:**
- Implement in 5+ languages
- Create fill-in-the-blank templates
- Write contrived examples
You're good at porting - one great example is enough.
## File Organization
### Self-Contained Skill
```
defense-in-depth/
SKILL.md # Everything inline
```
When: All content fits, no heavy reference needed
### Skill with Reusable Tool
```
condition-based-waiting/
SKILL.md # Overview + patterns
example.ts # Working helpers to adapt
```
When: Tool is reusable code, not just narrative
### Skill with Heavy Reference
```
pptx/
SKILL.md # Overview + workflows
pptxgenjs.md # 600 lines API reference
ooxml.md # 500 lines XML structure
scripts/ # Executable tools
```
When: Reference material too large for inline
## The Iron Law (Same as TDD)
```
NO SKILL WITHOUT A FAILING TEST FIRST
```
This applies to NEW skills AND EDITS to existing skills.
Write skill before testing? Delete it. Start over.
Edit skill without testing? Same violation.
**No exceptions:**
- Not for "simple additions"
- Not for "just adding a section"
- Not for "documentation updates"
- Don't keep untested changes as "reference"
- Don't "adapt" while running tests
- Delete means delete
**REQUIRED BACKGROUND:** The superpowers:test-driven-development skill explains why this matters. Same principles apply to documentation.
## Testing All Skill Types
Different skill types need different test approaches:
### Discipline-Enforcing Skills (rules/requirements)
**Examples:** TDD, verification-before-completion, designing-before-coding
**Test with:**
- Academic questions: Do they understand the rules?
- Pressure scenarios: Do they comply under stress?
- Multiple pressures combined: time + sunk cost + exhaustion
- Identify rationalizations and add explicit counters
**Success criteria:** Agent follows rule under maximum pressure
### Technique Skills (how-to guides)
**Examples:** condition-based-waiting, root-cause-tracing, defensive-programming
**Test with:**
- Application scenarios: Can they apply the technique correctly?
- Variation scenarios: Do they handle edge cases?
- Missing information tests: Do instructions have gaps?
**Success criteria:** Agent successfully applies technique to new scenario
### Pattern Skills (mental models)
**Examples:** reducing-complexity, information-hiding concepts
**Test with:**
- Recognition scenarios: Do they recognize when pattern applies?
- Application scenarios: Can they use the mental model?
- Counter-examples: Do they know when NOT to apply?
**Success criteria:** Agent correctly identifies when/how to apply pattern
### Reference Skills (documentation/APIs)
**Examples:** API documentation, command references, library guides
**Test with:**
- Retrieval scenarios: Can they find the right information?
- Application scenarios: Can they use what they found correctly?
- Gap testing: Are common use cases covered?
**Success criteria:** Agent finds and correctly applies reference information
## Common Rationalizations for Skipping Testing
| Excuse | Reality |
|--------|---------|
| "Skill is obviously clear" | Clear to you ≠ clear to other agents. Test it. |
| "It's just a reference" | References can have gaps, unclear sections. Test retrieval. |
| "Testing is overkill" | Untested skills have issues. Always. 15 min testing saves hours. |
| "I'll test if problems emerge" | Problems = agents can't use skill. Test BEFORE deploying. |
| "Too tedious to test" | Testing is less tedious than debugging bad skill in production. |
| "I'm confident it's good" | Overconfidence guarantees issues. Test anyway. |
| "Academic review is enough" | Reading ≠ using. Test application scenarios. |
| "No time to test" | Deploying untested skill wastes more time fixing it later. |
**All of these mean: Test before deploying. No exceptions.**
## Bulletproofing Skills Against Rationalization
Skills that enforce discipline (like TDD) need to resist rationalization. Agents are smart and will find loopholes when under pressure.
**Psychology note:** Understanding WHY persuasion techniques work helps you apply them systematically. See persuasion-principles.md for research foundation (Cialdini, 2021; Meincke et al., 2025) on authority, commitment, scarcity, social proof, and unity principles.
### Close Every Loophole Explicitly
Don't just state the rule - forbid specific workarounds:
<Bad>
```markdown
Write code before test? Delete it.
```
</Bad>
<Good>
```markdown
Write code before test? Delete it. Start over.
**No exceptions:**
- Don't keep it as "reference"
- Don't "adapt" it while writing tests
- Don't look at it
- Delete means delete
```
</Good>
### Address "Spirit vs Letter" Arguments
Add foundational principle early:
```markdown
**Violating the letter of the rules is violating the spirit of the rules.**
```
This cuts off entire class of "I'm following the spirit" rationalizations.
### Build Rationalization Table
Capture rationalizations from baseline testing (see Testing section below). Every excuse agents make goes in the table:
```markdown
| Excuse | Reality |
|--------|---------|
| "Too simple to test" | Simple code breaks. Test takes 30 seconds. |
| "I'll test after" | Tests passing immediately prove nothing. |
| "Tests after achieve same goals" | Tests-after = "what does this do?" Tests-first = "what should this do?" |
```
### Create Red Flags List
Make it easy for agents to self-check when rationalizing:
```markdown
## Red Flags - STOP and Start Over
- Code before test
- "I already manually tested it"
- "Tests after achieve the same purpose"
- "It's about spirit not ritual"
- "This is different because..."
**All of these mean: Delete code. Start over with TDD.**
```
### Update CSO for Violation Symptoms
Add to description: symptoms of when you're ABOUT to violate the rule:
```yaml
description: use when implementing any feature or bugfix, before writing implementation code
```
## RED-GREEN-REFACTOR for Skills
Follow the TDD cycle:
### RED: Write Failing Test (Baseline)
Run pressure scenario with subagent WITHOUT the skill. Document exact behavior:
- What choices did they make?
- What rationalizations did they use (verbatim)?
- Which pressures triggered violations?
This is "watch the test fail" - you must see what agents naturally do before writing the skill.
### GREEN: Write Minimal Skill
Write skill that addresses those specific rationalizations. Don't add extra content for hypothetical cases.
Run same scenarios WITH skill. Agent should now comply.
### REFACTOR: Close Loopholes
Agent found new rationalization? Add explicit counter. Re-test until bulletproof.
**REQUIRED SUB-SKILL:** Use superpowers:testing-skills-with-subagents for the complete testing methodology:
- How to write pressure scenarios
- Pressure types (time, sunk cost, authority, exhaustion)
- Plugging holes systematically
- Meta-testing techniques
## Anti-Patterns
### ❌ Narrative Example
"In session 2025-10-03, we found empty projectDir caused..."
**Why bad:** Too specific, not reusable
### ❌ Multi-Language Dilution
example-js.js, example-py.py, example-go.go
**Why bad:** Mediocre quality, maintenance burden
### ❌ Code in Flowcharts
```dot
step1 [label="import fs"];
step2 [label="read file"];
```
**Why bad:** Can't copy-paste, hard to read
### ❌ Generic Labels
helper1, helper2, step3, pattern4
**Why bad:** Labels should have semantic meaning
## STOP: Before Moving to Next Skill
**After writing ANY skill, you MUST STOP and complete the deployment process.**
**Do NOT:**
- Create multiple skills in batch without testing each
- Move to next skill before current one is verified
- Skip testing because "batching is more efficient"
**The deployment checklist below is MANDATORY for EACH skill.**
Deploying untested skills = deploying untested code. It's a violation of quality standards.
## Skill Creation Checklist (TDD Adapted)
**IMPORTANT: Use TodoWrite to create todos for EACH checklist item below.**
**RED Phase - Write Failing Test:**
- [ ] Create pressure scenarios (3+ combined pressures for discipline skills)
- [ ] Run scenarios WITHOUT skill - document baseline behavior verbatim
- [ ] Identify patterns in rationalizations/failures
**GREEN Phase - Write Minimal Skill:**
- [ ] Name uses only letters, numbers, hyphens (no parentheses/special chars)
- [ ] YAML frontmatter with only name and description (max 1024 chars)
- [ ] Description starts with "Use when..." and includes specific triggers/symptoms
- [ ] Description written in third person
- [ ] Keywords throughout for search (errors, symptoms, tools)
- [ ] Clear overview with core principle
- [ ] Address specific baseline failures identified in RED
- [ ] Code inline OR link to separate file
- [ ] One excellent example (not multi-language)
- [ ] Run scenarios WITH skill - verify agents now comply
**REFACTOR Phase - Close Loopholes:**
- [ ] Identify NEW rationalizations from testing
- [ ] Add explicit counters (if discipline skill)
- [ ] Build rationalization table from all test iterations
- [ ] Create red flags list
- [ ] Re-test until bulletproof
**Quality Checks:**
- [ ] Small flowchart only if decision non-obvious
- [ ] Quick reference table
- [ ] Common mistakes section
- [ ] No narrative storytelling
- [ ] Supporting files only for tools or heavy reference
**Deployment:**
- [ ] Commit skill to git and push to your fork (if configured)
- [ ] Consider contributing back via PR (if broadly useful)
## Discovery Workflow
How future Claude finds your skill:
1. **Encounters problem** ("tests are flaky")
3. **Finds SKILL** (description matches)
4. **Scans overview** (is this relevant?)
5. **Reads patterns** (quick reference table)
6. **Loads example** (only when implementing)
**Optimize for this flow** - put searchable terms early and often.
## The Bottom Line
**Creating skills IS TDD for process documentation.**
Same Iron Law: No skill without failing test first.
Same cycle: RED (baseline) → GREEN (write skill) → REFACTOR (close loopholes).
Same benefits: Better quality, fewer surprises, bulletproof results.
If you follow TDD for code, follow it for skills. It's the same discipline applied to documentation.

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digraph STYLE_GUIDE {
// The style guide for our process DSL, written in the DSL itself
// Node type examples with their shapes
subgraph cluster_node_types {
label="NODE TYPES AND SHAPES";
// Questions are diamonds
"Is this a question?" [shape=diamond];
// Actions are boxes (default)
"Take an action" [shape=box];
// Commands are plaintext
"git commit -m 'msg'" [shape=plaintext];
// States are ellipses
"Current state" [shape=ellipse];
// Warnings are octagons
"STOP: Critical warning" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
// Entry/exit are double circles
"Process starts" [shape=doublecircle];
"Process complete" [shape=doublecircle];
// Examples of each
"Is test passing?" [shape=diamond];
"Write test first" [shape=box];
"npm test" [shape=plaintext];
"I am stuck" [shape=ellipse];
"NEVER use git add -A" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
}
// Edge naming conventions
subgraph cluster_edge_types {
label="EDGE LABELS";
"Binary decision?" [shape=diamond];
"Yes path" [shape=box];
"No path" [shape=box];
"Binary decision?" -> "Yes path" [label="yes"];
"Binary decision?" -> "No path" [label="no"];
"Multiple choice?" [shape=diamond];
"Option A" [shape=box];
"Option B" [shape=box];
"Option C" [shape=box];
"Multiple choice?" -> "Option A" [label="condition A"];
"Multiple choice?" -> "Option B" [label="condition B"];
"Multiple choice?" -> "Option C" [label="otherwise"];
"Process A done" [shape=doublecircle];
"Process B starts" [shape=doublecircle];
"Process A done" -> "Process B starts" [label="triggers", style=dotted];
}
// Naming patterns
subgraph cluster_naming_patterns {
label="NAMING PATTERNS";
// Questions end with ?
"Should I do X?";
"Can this be Y?";
"Is Z true?";
"Have I done W?";
// Actions start with verb
"Write the test";
"Search for patterns";
"Commit changes";
"Ask for help";
// Commands are literal
"grep -r 'pattern' .";
"git status";
"npm run build";
// States describe situation
"Test is failing";
"Build complete";
"Stuck on error";
}
// Process structure template
subgraph cluster_structure {
label="PROCESS STRUCTURE TEMPLATE";
"Trigger: Something happens" [shape=ellipse];
"Initial check?" [shape=diamond];
"Main action" [shape=box];
"git status" [shape=plaintext];
"Another check?" [shape=diamond];
"Alternative action" [shape=box];
"STOP: Don't do this" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
"Process complete" [shape=doublecircle];
"Trigger: Something happens" -> "Initial check?";
"Initial check?" -> "Main action" [label="yes"];
"Initial check?" -> "Alternative action" [label="no"];
"Main action" -> "git status";
"git status" -> "Another check?";
"Another check?" -> "Process complete" [label="ok"];
"Another check?" -> "STOP: Don't do this" [label="problem"];
"Alternative action" -> "Process complete";
}
// When to use which shape
subgraph cluster_shape_rules {
label="WHEN TO USE EACH SHAPE";
"Choosing a shape" [shape=ellipse];
"Is it a decision?" [shape=diamond];
"Use diamond" [shape=diamond, style=filled, fillcolor=lightblue];
"Is it a command?" [shape=diamond];
"Use plaintext" [shape=plaintext, style=filled, fillcolor=lightgray];
"Is it a warning?" [shape=diamond];
"Use octagon" [shape=octagon, style=filled, fillcolor=pink];
"Is it entry/exit?" [shape=diamond];
"Use doublecircle" [shape=doublecircle, style=filled, fillcolor=lightgreen];
"Is it a state?" [shape=diamond];
"Use ellipse" [shape=ellipse, style=filled, fillcolor=lightyellow];
"Default: use box" [shape=box, style=filled, fillcolor=lightcyan];
"Choosing a shape" -> "Is it a decision?";
"Is it a decision?" -> "Use diamond" [label="yes"];
"Is it a decision?" -> "Is it a command?" [label="no"];
"Is it a command?" -> "Use plaintext" [label="yes"];
"Is it a command?" -> "Is it a warning?" [label="no"];
"Is it a warning?" -> "Use octagon" [label="yes"];
"Is it a warning?" -> "Is it entry/exit?" [label="no"];
"Is it entry/exit?" -> "Use doublecircle" [label="yes"];
"Is it entry/exit?" -> "Is it a state?" [label="no"];
"Is it a state?" -> "Use ellipse" [label="yes"];
"Is it a state?" -> "Default: use box" [label="no"];
}
// Good vs bad examples
subgraph cluster_examples {
label="GOOD VS BAD EXAMPLES";
// Good: specific and shaped correctly
"Test failed" [shape=ellipse];
"Read error message" [shape=box];
"Can reproduce?" [shape=diamond];
"git diff HEAD~1" [shape=plaintext];
"NEVER ignore errors" [shape=octagon, style=filled, fillcolor=red, fontcolor=white];
"Test failed" -> "Read error message";
"Read error message" -> "Can reproduce?";
"Can reproduce?" -> "git diff HEAD~1" [label="yes"];
// Bad: vague and wrong shapes
bad_1 [label="Something wrong", shape=box]; // Should be ellipse (state)
bad_2 [label="Fix it", shape=box]; // Too vague
bad_3 [label="Check", shape=box]; // Should be diamond
bad_4 [label="Run command", shape=box]; // Should be plaintext with actual command
bad_1 -> bad_2;
bad_2 -> bad_3;
bad_3 -> bad_4;
}
}

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# Persuasion Principles for Skill Design
## Overview
LLMs respond to the same persuasion principles as humans. Understanding this psychology helps you design more effective skills - not to manipulate, but to ensure critical practices are followed even under pressure.
**Research foundation:** Meincke et al. (2025) tested 7 persuasion principles with N=28,000 AI conversations. Persuasion techniques more than doubled compliance rates (33% → 72%, p < .001).
## The Seven Principles
### 1. Authority
**What it is:** Deference to expertise, credentials, or official sources.
**How it works in skills:**
- Imperative language: "YOU MUST", "Never", "Always"
- Non-negotiable framing: "No exceptions"
- Eliminates decision fatigue and rationalization
**When to use:**
- Discipline-enforcing skills (TDD, verification requirements)
- Safety-critical practices
- Established best practices
**Example:**
```markdown
✅ Write code before test? Delete it. Start over. No exceptions.
❌ Consider writing tests first when feasible.
```
### 2. Commitment
**What it is:** Consistency with prior actions, statements, or public declarations.
**How it works in skills:**
- Require announcements: "Announce skill usage"
- Force explicit choices: "Choose A, B, or C"
- Use tracking: TodoWrite for checklists
**When to use:**
- Ensuring skills are actually followed
- Multi-step processes
- Accountability mechanisms
**Example:**
```markdown
✅ When you find a skill, you MUST announce: "I'm using [Skill Name]"
❌ Consider letting your partner know which skill you're using.
```
### 3. Scarcity
**What it is:** Urgency from time limits or limited availability.
**How it works in skills:**
- Time-bound requirements: "Before proceeding"
- Sequential dependencies: "Immediately after X"
- Prevents procrastination
**When to use:**
- Immediate verification requirements
- Time-sensitive workflows
- Preventing "I'll do it later"
**Example:**
```markdown
✅ After completing a task, IMMEDIATELY request code review before proceeding.
❌ You can review code when convenient.
```
### 4. Social Proof
**What it is:** Conformity to what others do or what's considered normal.
**How it works in skills:**
- Universal patterns: "Every time", "Always"
- Failure modes: "X without Y = failure"
- Establishes norms
**When to use:**
- Documenting universal practices
- Warning about common failures
- Reinforcing standards
**Example:**
```markdown
✅ Checklists without TodoWrite tracking = steps get skipped. Every time.
❌ Some people find TodoWrite helpful for checklists.
```
### 5. Unity
**What it is:** Shared identity, "we-ness", in-group belonging.
**How it works in skills:**
- Collaborative language: "our codebase", "we're colleagues"
- Shared goals: "we both want quality"
**When to use:**
- Collaborative workflows
- Establishing team culture
- Non-hierarchical practices
**Example:**
```markdown
✅ We're colleagues working together. I need your honest technical judgment.
❌ You should probably tell me if I'm wrong.
```
### 6. Reciprocity
**What it is:** Obligation to return benefits received.
**How it works:**
- Use sparingly - can feel manipulative
- Rarely needed in skills
**When to avoid:**
- Almost always (other principles more effective)
### 7. Liking
**What it is:** Preference for cooperating with those we like.
**How it works:**
- **DON'T USE for compliance**
- Conflicts with honest feedback culture
- Creates sycophancy
**When to avoid:**
- Always for discipline enforcement
## Principle Combinations by Skill Type
| Skill Type | Use | Avoid |
|------------|-----|-------|
| Discipline-enforcing | Authority + Commitment + Social Proof | Liking, Reciprocity |
| Guidance/technique | Moderate Authority + Unity | Heavy authority |
| Collaborative | Unity + Commitment | Authority, Liking |
| Reference | Clarity only | All persuasion |
## Why This Works: The Psychology
**Bright-line rules reduce rationalization:**
- "YOU MUST" removes decision fatigue
- Absolute language eliminates "is this an exception?" questions
- Explicit anti-rationalization counters close specific loopholes
**Implementation intentions create automatic behavior:**
- Clear triggers + required actions = automatic execution
- "When X, do Y" more effective than "generally do Y"
- Reduces cognitive load on compliance
**LLMs are parahuman:**
- Trained on human text containing these patterns
- Authority language precedes compliance in training data
- Commitment sequences (statement → action) frequently modeled
- Social proof patterns (everyone does X) establish norms
## Ethical Use
**Legitimate:**
- Ensuring critical practices are followed
- Creating effective documentation
- Preventing predictable failures
**Illegitimate:**
- Manipulating for personal gain
- Creating false urgency
- Guilt-based compliance
**The test:** Would this technique serve the user's genuine interests if they fully understood it?
## Research Citations
**Cialdini, R. B. (2021).** *Influence: The Psychology of Persuasion (New and Expanded).* Harper Business.
- Seven principles of persuasion
- Empirical foundation for influence research
**Meincke, L., Shapiro, D., Duckworth, A. L., Mollick, E., Mollick, L., & Cialdini, R. (2025).** Call Me A Jerk: Persuading AI to Comply with Objectionable Requests. University of Pennsylvania.
- Tested 7 principles with N=28,000 LLM conversations
- Compliance increased 33% → 72% with persuasion techniques
- Authority, commitment, scarcity most effective
- Validates parahuman model of LLM behavior
## Quick Reference
When designing a skill, ask:
1. **What type is it?** (Discipline vs. guidance vs. reference)
2. **What behavior am I trying to change?**
3. **Which principle(s) apply?** (Usually authority + commitment for discipline)
4. **Am I combining too many?** (Don't use all seven)
5. **Is this ethical?** (Serves user's genuine interests?)