Four-phase debugging framework that finds root causes before proposing fixes. Use when investigating bugs, errors, unexpected behavior, failed tests, or when previous fixes haven't worked.
Applies a four-phase framework to systematically find root causes before proposing fixes.
/plugin marketplace add rileyhilliard/claude-essentials/plugin install ce@claude-essentialsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
references/debugging-techniques.mdCore principle: Find root cause before attempting fixes. Symptom fixes are failure.
Complete each phase before proceeding to the next.
Debugging Progress:
- [ ] Phase 1: Root Cause Investigation
- [ ] Phase 2: Pattern Analysis
- [ ] Phase 3: Hypothesis Testing
- [ ] Phase 4: Implementation
Before attempting ANY fix:
For multi-component systems: Add diagnostic logging at each component boundary before proposing fixes. See references/debugging-techniques.md for instrumentation patterns.
For log-heavy investigations: Use Skill(ce:reading-logs) for efficient analysis.
If 3+ fixes have failed: Stop fixing symptoms. Question the architecture.
Stop and return to Phase 1 if you catch yourself:
For specific debugging methods, see references/debugging-techniques.md:
## Root Cause
[1-3 sentences explaining underlying issue]
Located in: `file.ts:123`
## What Was Wrong
[Specific problem - mutation, race condition, missing validation, etc.]
## The Fix
[Changes made and why they address root cause]
## Verification
- [x] Bug reproduced and confirmed fixed
- [x] Existing tests pass
- [x] Added regression test
Search, retrieve, and install Agent Skills from the prompts.chat registry using MCP tools. Use when the user asks to find skills, browse skill catalogs, install a skill for Claude, or extend Claude's capabilities with reusable AI agent components.
Activates when the user asks about AI prompts, needs prompt templates, wants to search for prompts, or mentions prompts.chat. Use for discovering, retrieving, and improving prompts.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.