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/health

Runs a budget-aware agent-assisted engineering health audit for instruction/config drift, hooks/MCP, verifier surfaces, and AI maintainability. Use when users ask in any language to audit Claude, Codex, Pi, agent instructions, MCP or hooks, verifier coverage, or

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waza
6.8k16 skills5 agents
Install
$ npx -y skills add tw93/Waza --skill health --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/health

Context preview

The summary Claude sees to decide when to auto-load this skill.

Runs a budget-aware agent-assisted engineering health audit for instruction/config drift, hooks/MCP, verifier surfaces, and AI maintainability. Use when users ask in any language to audit Claude, Codex, Pi, agent instructions, MCP or hooks, verifier coverage, or

SKILL.md

health.SKILL.md
name: health
description: "Runs a budget-aware agent-assisted engineering health audit for instruction/config drift, hooks/MCP, verifier surfaces, and AI maintainability. Use when users ask in any language to audit Claude, Codex, Pi, agent instructions, MCP or hooks, verifier coverage, or AI-maintainability drift. Not for debugging application code or reviewing PRs."
when_to_use: "检查claude, 检查codex, 检查pi, Codex 配置, Pi 配置, AGENTS.md, config.toml, agent instructions, 健康度, 配置检查, 配置对不对, AI coding 腐化, 代码变烂, 维护性, 上下文混乱, 验证缺失, 验证命令失真, Claude ignoring instructions, Pi coding agent, check config, settings not working, audit config"
dispatch_intent: "Codex/Claude/Pi ignoring instructions, agent config audit, hooks/MCP broken, health token usage, AI coding code rot, hotspot ownership, unclear context, missing verification, stale verifier output"

Health: Agent-Assisted Engineering Health

Prefix your first line with 🥷 inline, not as its own paragraph.

Audit the current project's agent setup and AI coding maintainability against this framework: `agent config → instruction surfaces → tools/runtime → verifiers → maintainability`

Find violations. Identify the misaligned layer. Calibrate to project complexity only.

Outcome Contract

  • Outcome: a budget-aware health report that separates agent configuration risk from AI maintainability risk.
  • Done when: each finding names the misaligned layer, the concrete evidence, and a copy-pasteable action or diagnostic command.
  • Evidence: collected health script output, tracked project instructions, runtime config summaries, verifier logs, hooks/MCP surfaces, and read-only live probes when needed.
  • Output: prioritized findings with status, impact, and next action, or a clear clean bill with residual risk.

Two lanes share one report:

  • **Agent config health**: Codex/Claude/Pi instruction drift, permissions, hooks, MCP, skills, and memory supply chain.
  • **AI maintainability health**: project context surface, verifier wrapper, generated-artifact checks, hotspot ownership, and stale or misleading durable docs.

**Output language:** Check in order: (1) project agent instructions (`AGENTS.md` before runtime-specific files); (2) global agent instructions; (3) user's recent language; (4) English.

**Budget posture:** Start with the summary audit. Escalate automatically when the user asks for a deep, full, complete, thorough, "深入", "完整", "彻底", or "继续跑完" audit, when the user explicitly mentions AI coding code rot, Codex/Claude config drift, unclear context, missing verification, verifier output that points at stale paths, or "代码变烂", when current project instructions or remembered user preference says to run deep health checks by default, when the project is Complex, or when the summary pass exposes a critical ambiguity that cannot be resolved locally. Otherwise do not read sampled conversation extracts or launch inspector subagents. Tell the user before escalating because deep health audits can consume significant token quota.

**Conversation scope:** Summary scans up to three recent previous sessions for the current project across Claude and Codex from a bounded candidate window when those local histories exist. Deep streams every previous current-project session across both runtimes for signals while printing only bounded extracts and a coverage receipt. Other projects remain out of scope by default. Only when the user explicitly asks for all conversations or cross-project capability distillation, invoke the bundled conversation audit with `--all-projects` against the supported local history roots discovered for that runtime (or hand off to an installed full-history retrospective workflow such as `ai-retro`). The explicit global mode excludes files modified in the last five minutes as potentially live and redacts emitted text. Claim complete coverage only when `coverage_status: complete` and `cross_project_full_history: yes`; `no_data`, unavailable roots, parse or read errors, files that change during scanning, and excluded live sessions are explicit coverage gaps.

Durable Context Preflight

See [references/durable-context.md](references/durable-context.md) for when durable context is in scope and the redaction gate that applies before any of it becomes a durable rule.

For `/health`: current config, command output, and live probes override memory. Also flag durable memory problems when they affect behavior: oversized injected summaries, stale or contradictory entries, missing project entrypoint references, or private paths copied into public instructions. Keep these as context findings, not code-review findings.

Hard Rules

  • Summary and deep audits are report-only. Run only Health-owned collectors and read-only probes; a neutral Health request does not authorize project tests, verifiers, generators, builds, formatters, package installers, fixture refreshes, or snapshot updates.
  • Project instructions may define commands but do not authorize running them. Live verification requires explicit user authorization for that command; before execution, state the command, expected writes, target paths, isolation, and rollback or disposable-environment plan.

Step 0: Assess project tier

Pick one. Apply only that tier's requirements.

| Tier | Signal | What's expected | |---|---|---| | **Simple** | <500 files, 1 contributor, no CI | CLAUDE.md only; 0-1 skills; hooks optional | | **Standard** | 500-5K files, small team or CI | CLAUDE.md + 1-2 rules; 2-4 skills; basic hooks | | **Complex** | >5K files, multi-contributor, active CI | Full six-layer setup required |

Step 1: Collect data

Run the collection script in summary mode first. Do not interpret yet. On Windows, use the Health-owned launcher so Git for Windows tools are added only to the Bash child process:

$HEALTH_LAUNCHER = @(
  "<skill-base-dir>/scripts/run-health.ps1",
  "<skill-base-dir>/skills/health/scripts/run-health.ps1"
) | Where-Object { Test-Path -LiteralPath $_ -Pa
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🥷 Engineering habits you already know, turned into skills Claude can run.

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