gh-cipherstash-cipherpowers-plugin/skills/selecting-agents/SKILL.md

name, description, when_to_use, version

name	description	when_to_use	version
Selecting Agents	Decision guide for choosing the right specialized agent for each task type	before dispatching work to specialized agents, when multiple agents could apply	1.0.0

Selecting Agents

Overview

Use the right agent for the job. Each agent is optimized for specific scenarios and follows a focused workflow.

This skill helps you choose which specialized agent to use based on the task at hand.

For automatic agent selection: When executing implementation plans, use the /cipherpowers:execute command which applies this skill's logic automatically with hybrid keyword/LLM analysis. Manual selection using this skill is for ad-hoc agent dispatch outside of plan execution.

Agent Selection Logic

When selecting agents (manually or automatically), you must analyze the task requirements and context, not just match keywords naively.

DO NOT use naive keyword matching:

• ❌ Task contains "ultrathink" → select ultrathink-debugger
• ❌ Task contains "rust" → select rust-agent
• ❌ Task mentions agent name → select that agent

DO use semantic understanding:

• ✅ Analyze what the task is asking for (debugging? implementation? review?)
• ✅ Consider task complexity and characteristics
• ✅ Match agent capabilities to task requirements
• ✅ Ignore mentions of agent names that are not prescriptive

Examples of INCORRECT selection:

• Task: "Fix simple bug (don't use ultrathink-debugger, it's overkill)" → ❌ Selecting ultrathink-debugger because "ultrathink" appears
• Task: "Implement feature X in Python (not Rust)" → ❌ Selecting rust-agent because "rust" appears
• Task: "Add tests like the code-review-agent suggested" → ❌ Selecting code-review-agent because it's mentioned

Examples of CORRECT selection:

• Task: "Fix simple bug in auth.py" → ✅ general-purpose (simple bug, not complex)
• Task: "Investigate random CI failures with timing issues" → ✅ ultrathink-debugger (complex, timing, environment-specific)
• Task: "Add new endpoint to user service (Rust)" → ✅ rust-agent (Rust implementation work)
• Task: "Don't use ultrathink for this simple validation fix" → ✅ general-purpose (task explicitly says it's simple)

Selection criteria:

1. What is the task type? (implementation, debugging, review, documentation)
2. What is the complexity? (simple fix vs multi-component investigation)
3. What technology? (Rust code vs other languages)
4. What is explicitly requested? (user prescribing specific agent vs mentioning in passing)

Red flags that indicate you're selecting incorrectly:

• Selected agent based on keyword appearance alone
• Ignored explicit guidance in task description (e.g., "don't use X")
• Selected debugging agent for simple implementation task
• Selected specialized agent when general-purpose is more appropriate

Documentation Agents

technical-writer

When to use: After code changes that affect documentation

Scenarios:

• Updated API endpoints, added new features
• Changed configuration options or environment variables
• Modified architecture or system design
• Refactored code that impacts user-facing docs
• Added new commands, tools, or workflows

Skill used: maintaining-docs-after-changes

Command: /cipherpowers:verify docs

Key characteristic: Reactive to code changes - syncs docs with current code state

Debugging Agents

ultrathink-debugger

When to use: Complex, multi-layered debugging requiring deep investigation

Scenarios:

• Production failures with complex symptoms
• Environment-specific issues (works locally, fails in production/CI/Azure)
• Multi-component system failures (API → service → database)
• Integration problems (external APIs, third-party services)
• Timing and concurrency issues (race conditions, intermittent failures)
• Mysterious behavior resisting standard debugging

Skills used: systematic-debugging, root-cause-tracing, defense-in-depth, verification-before-completion

Key characteristic: Opus-level investigation for complex scenarios, not simple bugs

Development Agents

rust-agent

When to use: Rust development tasks requiring TDD and code review discipline

Scenarios:

• Implementing new Rust features
• Refactoring Rust code
• Performance optimization
• Systems programming tasks
• Any Rust development work

Skills used: test-driven-development, testing-anti-patterns, code-review-reception

Key characteristic: Enforces TDD, mandatory code review, project task usage

Review Agents

code-review-agent

When to use: Reviewing code changes before merging

Scenarios:

• Before completing feature implementation
• After addressing initial feedback
• When ready to merge to main branch

Skill used: conducting-code-review

Command: /cipherpowers:code-review

Key characteristic: Structured review process with severity levels (BLOCKING/NON-BLOCKING)

plan-review-agent

When to use: Evaluating implementation plans before execution

Scenarios:

• After writing a plan with /cipherpowers:plan
• Before executing a plan with /cipherpowers:execute
• When plan quality needs validation
• When plan scope or approach is uncertain

Skill used: verifying-plans

Command: /cipherpowers:verify plan

Key characteristic: Evaluates plan against 35 quality criteria across 6 categories (Security, Testing, Architecture, Error Handling, Code Quality, Process)

Common Confusions

Confusion	Correct Choice	Why
"Just finished feature, need docs"	technical-writer + /summarise	technical-writer syncs API/feature docs, /summarise captures learning
"Quick docs update"	technical-writer	All doc maintenance uses systematic process
"Fixed bug, should document"	/summarise command	Capturing what you learned, not updating technical docs
"Changed README"	Depends	Updated feature docs = technical-writer. Captured work summary = /summarise
"Production debugging done"	/summarise command	Document the investigation insights and lessons learned

Selection Examples

Scenario 1: Added new API endpoint → technical-writer - Code changed, docs need sync

Scenario 2: Spent 3 hours debugging Azure timeout → /summarise command - Capture the investigation, decisions, solution

Scenario 3: Both apply - finished user authentication feature → technical-writer first - Update API docs, configuration guide → /summarise second - Capture why you chose OAuth2, what issues you hit

Scenario 4: Random test failures in CI → ultrathink-debugger - Complex timing/environment issue needs deep investigation

Scenario 5: Simple bug fix in Rust → rust-agent - Standard development workflow with TDD

Scenario 6: Just finished writing implementation plan → plan-review-agent - Validate plan before execution

Scenario 7: About to execute plan, want quality check → plan-review-agent - Ensure plan is comprehensive and executable

Remember

• Most completed work needs both documentation types (technical-writer agent for code sync, /summarise for learning)
• Use technical-writer when code changes
• Use /summarise command when work completes
• Use ultrathink-debugger for complex debugging (not simple bugs)
• Use rust-agent for all Rust development
• Use code-review-agent before merging code
• Use plan-review-agent before executing plans