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commands/create_plan.md
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451
commands/create_plan.md
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---
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description: Create detailed implementation plans through interactive research and iteration
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---
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# Implementation Plan
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You are tasked with creating detailed implementation plans through an interactive, iterative process. You should be skeptical, thorough, and work collaboratively with the user to produce high-quality technical specifications.
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## Initial Response
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When this command is invoked:
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1. **Check if parameters were provided**:
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- If a file path or ticket reference was provided as a parameter, skip the default message
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- Immediately read any provided files FULLY
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- Begin the research process
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2. **If no parameters provided**, respond with:
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```
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I'll help you create a detailed implementation plan. Let me start by understanding what we're building.
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Please provide:
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1. The task/ticket description (or reference to a ticket file)
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2. Any relevant context, constraints, or specific requirements
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3. Links to related research or previous implementations
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I'll analyze this information and work with you to create a comprehensive plan.
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Tip: You can also invoke this command with a requirements file directly: `/create_plan tasks/kasper-junge/001-2025-01-15-feature-name/requirements.md`
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For deeper analysis, try: `/create_plan think deeply about tasks/kasper-junge/001-2025-01-15-feature-name/requirements.md`
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```
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Then wait for the user's input.
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## Process Steps
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### Step 1: Context Gathering & Initial Analysis
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1. **Read all mentioned files immediately and FULLY**:
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- Requirements files (e.g., `tasks/<username>/001-2025-01-15-feature-name/requirements.md`)
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- Research documents from the task directory
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- Related implementation plans
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- Any JSON/data files mentioned
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- **IMPORTANT**: Use the Read tool WITHOUT limit/offset parameters to read entire files
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- **CRITICAL**: DO NOT spawn sub-tasks before reading these files yourself in the main context
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- **NEVER** read files partially - if a file is mentioned, read it completely
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2. **Spawn initial research tasks to gather context**:
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Before asking the user any questions, use specialized agents to research in parallel:
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- Use the **codebase-locator** agent to find all files related to the task
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- Use the **codebase-analyzer** agent to understand how the current implementation works
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These agents will:
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- Find relevant source files, configs, and tests
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- Identify the specific directories to focus on (e.g., if WUI is mentioned, they'll focus on humanlayer-wui/)
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- Trace data flow and key functions
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- Return detailed explanations with file:line references
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3. **Read all files identified by research tasks**:
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- After research tasks complete, read ALL files they identified as relevant
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- Read them FULLY into the main context
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- This ensures you have complete understanding before proceeding
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4. **Analyze and verify understanding**:
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- Cross-reference the task requirements with actual code
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- Identify any discrepancies or misunderstandings
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- Note assumptions that need verification
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- Determine true scope based on codebase reality
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5. **Present informed understanding and focused questions**:
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```
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Based on the requirements and my research of the codebase, I understand we need to [accurate summary].
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I've found that:
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- [Current implementation detail with file:line reference]
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- [Relevant pattern or constraint discovered]
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- [Potential complexity or edge case identified]
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Questions that my research couldn't answer:
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- [Specific technical question that requires human judgment]
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- [Business logic clarification]
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- [Design preference that affects implementation]
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```
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Only ask questions that you genuinely cannot answer through code investigation.
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### Step 2: Research & Discovery
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After getting initial clarifications:
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1. **If the user corrects any misunderstanding**:
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- DO NOT just accept the correction
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- Spawn new research tasks to verify the correct information
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- Read the specific files/directories they mention
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- Only proceed once you've verified the facts yourself
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2. **Create a research todo list** using TodoWrite to track exploration tasks
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3. **Spawn parallel sub-tasks for comprehensive research**:
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- Create multiple Task agents to research different aspects concurrently
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- Use the right agent for each type of research:
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**For deeper investigation:**
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- **codebase-locator** - To find more specific files (e.g., "find all files that handle [specific component]")
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- **codebase-analyzer** - To understand implementation details (e.g., "analyze how [system] works")
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- **codebase-pattern-finder** - To find similar features we can model after
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**For web research (if needed):**
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- **web-search-researcher** - To find external documentation, tutorials, or best practices
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Each agent knows how to:
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- Find the right files and code patterns
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- Identify conventions and patterns to follow
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- Look for integration points and dependencies
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- Return specific file:line references
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- Find tests and examples
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3. **Wait for ALL sub-tasks to complete** before proceeding
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4. **Present findings and design options**:
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```
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Based on my research, here's what I found:
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**Current State:**
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- [Key discovery about existing code]
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- [Pattern or convention to follow]
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**Design Options:**
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1. [Option A] - [pros/cons]
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2. [Option B] - [pros/cons]
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**Open Questions:**
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- [Technical uncertainty]
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- [Design decision needed]
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Which approach aligns best with your vision?
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```
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### Step 3: Plan Structure Development
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Once aligned on approach:
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1. **Create initial plan outline**:
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```
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Here's my proposed plan structure:
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## Overview
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[1-2 sentence summary]
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## Implementation Phases:
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1. [Phase name] - [what it accomplishes]
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2. [Phase name] - [what it accomplishes]
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3. [Phase name] - [what it accomplishes]
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Does this phasing make sense? Should I adjust the order or granularity?
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```
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2. **Get feedback on structure** before writing details
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### Step 4: Detailed Plan Writing
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After structure approval:
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1. **Determine username:**
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- Run the `${CLAUDE_PLUGIN_ROOT}/scripts/spec_metadata.sh` script if not already run
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- Check the script output for "Normalized Username"
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- If present → use it
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- If not present:
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- Check for "Existing Users" in the output
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- If existing users found → prompt: "Which user are you? [user1/user2/user3]: "
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- If no existing users → prompt: "Enter your name: " then normalize it (lowercase, spaces to hyphens)
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- Store the username for creating the directory path
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2. **Determine the task directory**:
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- If working on an existing task (e.g., research already exists), write to that task's directory: `tasks/<username>/NNN-YYYY-MM-DD-description/plan.md`
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- If starting a new task, create a new numbered directory:
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- Check what task numbers already exist in `tasks/<username>/`
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- Use the next sequential number (e.g., if tasks/kasper-junge/003-... exists, create tasks/kasper-junge/004-...)
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- Format: `tasks/<username>/NNN-YYYY-MM-DD-description/plan.md` where:
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- `<username>` is the normalized username (e.g., kasper-junge, jonas-peterson)
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- NNN is a zero-padded 3-digit number (001, 002, etc.) - per-user numbering
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- YYYY-MM-DD is today's date
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- description is a brief kebab-case description
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- Example: `tasks/kasper-junge/005-2025-01-15-add-authentication/plan.md`
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3. **Write the plan** to the task directory
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4. **Use this template structure**:
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````markdown
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# [Feature/Task Name] Implementation Plan
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## Overview
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[Brief description of what we're implementing and why]
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## Current State Analysis
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[What exists now, what's missing, key constraints discovered]
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## Desired End State
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[A Specification of the desired end state after this plan is complete, and how to verify it]
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### Key Discoveries:
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- [Important finding with file:line reference]
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- [Pattern to follow]
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- [Constraint to work within]
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## What We're NOT Doing
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[Explicitly list out-of-scope items to prevent scope creep]
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## Implementation Approach
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[High-level strategy and reasoning]
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## Phase 1: [Descriptive Name]
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### Overview
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[What this phase accomplishes]
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### Changes Required:
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#### 1. [Component/File Group]
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**File**: `path/to/file.ext`
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**Changes**: [Summary of changes]
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```[language]
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// Specific code to add/modify
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```
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### Success Criteria:
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#### Automated Verification:
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- [ ] Migration applies cleanly: `[project-specific command, e.g., python manage.py migrate]`
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- [ ] Unit tests pass: `[project-specific command, e.g., npm test, pytest tests/unit/]`
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- [ ] Type checking passes: `[if applicable, e.g., npm run typecheck, mypy src/]`
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- [ ] Linting passes: `[project-specific command, e.g., npm run lint, flake8 src/]`
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- [ ] Integration tests pass: `[project-specific command, e.g., npm run test:integration]`
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#### Manual Verification:
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- [ ] Feature works as expected when tested via UI
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- [ ] Performance is acceptable under load
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- [ ] Edge case handling verified manually
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- [ ] No regressions in related features
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**Implementation Note**: After completing this phase and all automated verification passes, pause here for manual confirmation from the human that the manual testing was successful before proceeding to the next phase.
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---
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## Phase 2: [Descriptive Name]
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[Similar structure with both automated and manual success criteria...]
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---
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## Testing Strategy
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### Unit Tests:
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- [What to test]
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- [Key edge cases]
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### Integration Tests:
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- [End-to-end scenarios]
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### Manual Testing Steps:
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1. [Specific step to verify feature]
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2. [Another verification step]
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3. [Edge case to test manually]
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## Performance Considerations
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[Any performance implications or optimizations needed]
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## Migration Notes
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[If applicable, how to handle existing data/systems]
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## References
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- Original requirements: `tasks/<username>/NNN-YYYY-MM-DD-description/requirements.md` (if applicable)
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- Related research: `tasks/<username>/NNN-YYYY-MM-DD-description/research.md` (if applicable)
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- Similar implementation: `[file:line]`
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````
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### Step 5: Review and Iterate
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1. **Present the draft plan location**:
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```
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I've created the initial implementation plan at:
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`tasks/<username>/NNN-YYYY-MM-DD-description/plan.md`
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Please review it and let me know:
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- Are the phases properly scoped?
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- Are the success criteria specific enough?
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- Any technical details that need adjustment?
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- Missing edge cases or considerations?
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```
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2. **Iterate based on feedback** - be ready to:
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- Add missing phases
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- Adjust technical approach
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- Clarify success criteria (both automated and manual)
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- Add/remove scope items
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3. **Continue refining** until the user is satisfied
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## Important Guidelines
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1. **Be Skeptical**:
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- Question vague requirements
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- Identify potential issues early
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- Ask "why" and "what about"
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- Don't assume - verify with code
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2. **Be Interactive**:
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- Don't write the full plan in one shot
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- Get buy-in at each major step
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- Allow course corrections
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- Work collaboratively
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3. **Be Thorough**:
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- Read all context files COMPLETELY before planning
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- Research actual code patterns using parallel sub-tasks
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- Include specific file paths and line numbers
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- Write measurable success criteria with clear automated vs manual distinction
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- Use the project's standard testing/verification commands in success criteria
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4. **Be Practical**:
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- Focus on incremental, testable changes
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- Consider migration and rollback
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- Think about edge cases
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- Include "what we're NOT doing"
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5. **Track Progress**:
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- Use TodoWrite to track planning tasks
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- Update todos as you complete research
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- Mark planning tasks complete when done
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6. **No Open Questions in Final Plan**:
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- If you encounter open questions during planning, STOP
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- Research or ask for clarification immediately
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- Do NOT write the plan with unresolved questions
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- The implementation plan must be complete and actionable
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- Every decision must be made before finalizing the plan
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## Success Criteria Guidelines
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**Always separate success criteria into two categories:**
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1. **Automated Verification** (can be run by execution agents):
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- Commands that can be run: `make test`, `npm run lint`, etc.
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- Specific files that should exist
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- Code compilation/type checking
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- Automated test suites
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2. **Manual Verification** (requires human testing):
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- UI/UX functionality
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- Performance under real conditions
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- Edge cases that are hard to automate
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- User acceptance criteria
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**Format example:**
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```markdown
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### Success Criteria:
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#### Automated Verification:
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- [ ] Database migration runs successfully: `python manage.py migrate`
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- [ ] All unit tests pass: `pytest tests/`
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- [ ] No linting errors: `flake8 src/`
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- [ ] API endpoint returns 200: `curl localhost:8080/api/new-endpoint`
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#### Manual Verification:
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- [ ] New feature appears correctly in the UI
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- [ ] Performance is acceptable with 1000+ items
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- [ ] Error messages are user-friendly
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- [ ] Feature works correctly on mobile devices
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```
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## Common Patterns
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### For Database Changes:
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- Start with schema/migration
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- Add store methods
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- Update business logic
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- Expose via API
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- Update clients
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### For New Features:
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- Research existing patterns first
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- Start with data model
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- Build backend logic
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- Add API endpoints
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- Implement UI last
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### For Refactoring:
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- Document current behavior
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- Plan incremental changes
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- Maintain backwards compatibility
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- Include migration strategy
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## Sub-task Spawning Best Practices
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When spawning research sub-tasks:
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1. **Spawn multiple tasks in parallel** for efficiency
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2. **Each task should be focused** on a specific area
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3. **Provide detailed instructions** including:
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- Exactly what to search for
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- Which directories to focus on
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- What information to extract
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- Expected output format
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4. **Be EXTREMELY specific about directories**:
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- If the requirements mention specific subsystems, specify those directories
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- Be explicit about directory paths in your research prompts
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- Include the full path context in your prompts
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5. **Specify read-only tools** to use
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6. **Request specific file:line references** in responses
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7. **Wait for all tasks to complete** before synthesizing
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8. **Verify sub-task results**:
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- If a sub-task returns unexpected results, spawn follow-up tasks
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- Cross-check findings against the actual codebase
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- Don't accept results that seem incorrect
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Example of spawning multiple tasks:
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```python
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# Spawn these tasks concurrently:
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tasks = [
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Task("Research database schema", db_research_prompt),
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Task("Find API patterns", api_research_prompt),
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Task("Investigate UI components", ui_research_prompt),
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Task("Check test patterns", test_research_prompt)
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]
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```
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## Example Interaction Flow
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```
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User: /implementation_plan
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Assistant: I'll help you create a detailed implementation plan...
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User: We need to add authentication to the API. See tasks/kasper-junge/003-2025-01-10-api-auth/requirements.md
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Assistant: Let me read that requirements file completely first...
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[Reads file fully]
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Based on the requirements, I understand we need to add JWT-based authentication to the API endpoints. Before I start planning, I have some questions...
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[Interactive process continues...]
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```
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Reference in New Issue
Block a user