project-health
npx skills add https://github.com/jezweb/claude-skills --skill project-health
Agent 安装分布
Skill 文档
Project Health: AI-Agent Readiness Auditing
Status: Active Updated: 2026-01-30 Focus: Ensuring documentation and workflows are executable by AI agents
Overview
This skill evaluates project health from an AI-agent perspective – not just whether docs are well-written for humans, but whether future Claude Code sessions can:
- Understand the documentation without ambiguity
- Execute workflows by following instructions literally
- Resume work effectively with proper context handoff
When to Use
- Before handing off a project to another AI session
- When onboarding AI agents to contribute to a codebase
- After major refactors to ensure docs are still AI-executable
- When workflows fail because agents “didn’t understand”
- Periodic health checks for AI-maintained projects
Agent Selection Guide
| Situation | Use Agent | Why |
|---|---|---|
| “Will another Claude session understand this?” | context-auditor | Checks for ambiguous references, implicit knowledge, incomplete examples |
| “Will this workflow actually execute?” | workflow-validator | Verifies steps are discrete, ordered, and include verification |
| “Can a new session pick up where I left off?” | handoff-checker | Validates SESSION.md, phase tracking, context preservation |
| Full project health audit | All three | Comprehensive AI-readiness assessment |
Key Principles
1. Literal Interpretation
AI agents follow instructions literally. Documentation that works for humans (who fill in gaps) may fail for agents.
Human-friendly (ambiguous):
“Update the config file with your settings”
AI-friendly (explicit):
“Edit
wrangler.jsoncand setaccount_idto your Cloudflare account ID (find it at dash.cloudflare.com â Overview â Account ID)”
2. Explicit Over Implicit
Never assume the agent knows:
- Which file you mean
- What “obvious” next steps are
- Environment state or prerequisites
- What success looks like
3. Verification at Every Step
Agents can’t tell if something “feels right”. Include verification:
- Expected output after each command
- How to check if a step succeeded
- What to do if it failed
Agents
context-auditor
Purpose: Evaluate AI-readability of documentation
Checks:
- Instructions use imperative verbs (actionable)
- File paths are explicit (not “the config file”)
- Success criteria are measurable
- No ambiguous references (“that thing”, “as discussed”)
- Code examples are complete (not fragments)
- Dependencies/prerequisites stated explicitly
- Error handling documented
Output: AI-Readability Score (0-100) with specific issues
workflow-validator
Purpose: Verify processes are executable when followed literally
Checks:
- Steps are discrete and ordered
- Each step has clear input/output
- No implicit knowledge required
- Environment assumptions documented
- Verification step after each action
- Failure modes and recovery documented
- No “obvious” steps omitted
Output: Executability Score (0-100) with step-by-step analysis
handoff-checker
Purpose: Ensure session continuity for multi-session work
Checks:
- SESSION.md or equivalent exists
- Current phase/status clear
- Next actions documented
- Blockers/decisions needed listed
- Context for future sessions preserved
- Git checkpoint pattern in use
- Architecture decisions documented with rationale
Output: Handoff Quality Score (0-100) with continuity gaps
Templates
AI-Readable Documentation Template
See templates/AI_READABLE_DOC.md for a template that ensures AI-readability.
Key sections:
- Prerequisites (explicit environment/state requirements)
- Steps (numbered, discrete, with verification)
- Expected Output (what success looks like)
- Troubleshooting (common failures and fixes)
Handoff Checklist
See templates/HANDOFF_CHECKLIST.md for ensuring clean session handoffs.
Anti-Patterns
1. “See Above” References
# Bad
As mentioned above, configure the database.
# Good
Configure the database by running:
`npx wrangler d1 create my-db`
2. Implicit File Paths
# Bad
Update the config with your API key.
# Good
Add your API key to `.dev.vars`:
API_KEY=your-key-here
3. Missing Verification
# Bad
Run the migration.
# Good
Run the migration:
`npx wrangler d1 migrations apply my-db --local`
Verify with:
`npx wrangler d1 execute my-db --local --command "SELECT name FROM sqlite_master WHERE type='table'"`
Expected output: Should show your table names.
4. Assumed Context
# Bad
Now deploy (you know the drill).
# Good
Deploy to production:
`npx wrangler deploy`
Verify deployment at: https://your-worker.your-subdomain.workers.dev
Relationship to Other Tools
| Tool | Focus | Audience |
|---|---|---|
project-docs-auditor |
Traditional doc quality (links, freshness, structure) | Human readers |
project-health skill |
AI-agent readiness (executability, clarity, handoff) | Claude sessions |
docs-workflow skill |
Creating/managing specific doc files | Both |
Quick Start
- Full audit: “Run all project-health agents on this repo”
- Check one aspect: “Use context-auditor to check AI-readability”
- Before handoff: “Use handoff-checker before I end this session”
Success Metrics
A healthy project scores:
- Context Auditor: 80+ (AI can understand without clarification)
- Workflow Validator: 90+ (steps execute literally without failure)
- Handoff Checker: 85+ (new session can resume immediately)
Projects below these thresholds have documentation debt that will slow future AI sessions.