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Pulz

Feel the pulse of your code.

Pulz is an Agent Skill that guides LLM / Coding Agents to diagnose and fix code bugs using Traditional Chinese Medicine (TCM) diagnostic methodology.

Instead of jumping to a fix, Pulz enforces a structured four-phase examination -- Observation, Listening, Inquiry, Palpation -- to fully understand a bug before prescribing a minimal-invasive repair. The core philosophy: treat the root cause, not the symptom.

How It Works

Phase TCM Concept What the Agent Does
1. Observation Wang-Zhen Static code analysis: structure, complexity, code smells
2. Listening Wen-Zhen Runtime signal analysis: logs, errors, performance data
3. Inquiry Wen-Zhen (Inquiry) Context collection: environment, recent changes, reproduction conditions
4. Palpation Qie-Zhen Dynamic debugging: reproduction tests, data flow tracing
Diagnosis Bian-Zheng Synthesize findings into a Bug Profile
Treatment Shi-Zhi Generate minimal-invasive fix with reproduction test

Quick Start

Use with any Agent Skills-compatible tool

Copy the pulz/ directory into your project or agent's skill discovery path:

cp -r pulz/ /path/to/your/skills/

Directory Structure

pulz/
  SKILL.md                               # Core skill instructions
  references/
    OBSERVATION-GUIDE.md                  # Phase 1: static analysis checklist
    LISTENING-GUIDE.md                    # Phase 2: error pattern catalog
    INQUIRY-GUIDE.md                      # Phase 3: question templates
    PALPATION-GUIDE.md                    # Phase 4: debugging strategies
  assets/
    diagnosis-report-template.md          # Structured output template

Usage with Claude Code

Place the pulz/ directory under .claude/skills/ in your project root:

.claude/skills/pulz/SKILL.md

Usage with other agents

Place the pulz/ directory where your agent discovers skills. Refer to your agent's documentation for the appropriate path.

Design Reference

See spec.md for the complete design specification, including planned features beyond bug fixing (visualization, CI/CD integration, adaptive learning, etc.).

License

MIT

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