health

health is a skill for Claude Code from tw93/Waza. It costs 40 tokens per session (4,506 once invoked), scanned A, original, MIT.

An engineering health audit for AI coding environments, covering instructions, configuration, tools, hooks, verifiers, and maintainability. It produces evidence-based findings with priorities and suggested actions.

In plain words
What is it for?
Use it to audit Codex, Claude, or Pi setups, inspect MCP tools and hooks, assess verifier coverage, and identify concrete fixes for AI maintainability risks.
Why use it?
It reveals configuration drift, missing checks, weak verification, and other issues that can make agent-assisted development unsafe or hard to maintain.

Skill for Claude Code

Written for Claude Code: when-to-use in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Good fit Use it to audit Codex, Claude, or Pi setups, inspect MCP tools and hooks, assess verifier coverage, and identify concrete fixes for AI maintainability risks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tw93/waza/health
View source ↗ tw93/Waza
About the project

Waza is a collection of installed skills that turn familiar engineering practices into repeatable playbooks for coding agents. It helps agents plan work, design interfaces, review changes, debug problems, edit prose, research unfamiliar subjects, read URLs or PDFs, and check their own health. The catalogue entries are Waza’s skills and supporting agents or instructions.

tw93/Waza · 7,355 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add tw93/Waza --skill health
Clone the repo
git clone --depth 1 https://github.com/tw93/Waza

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for health

README.md
[![agentmods](https://agentmods.dev/badge/skills/tw93/waza/health/github.svg)](https://agentmods.dev/skills/tw93/waza/health)
Your own site
<a href="https://agentmods.dev/skills/tw93/waza/health"><img src="https://agentmods.dev/badge/skills/tw93/waza/health/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for health

Your own site · 80×15
<a href="https://agentmods.dev/skills/tw93/waza/health"><img src="https://agentmods.dev/badge/skills/tw93/waza/health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,506 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 15 Oct 2026
  • Snyk pass 15 Oct 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 6 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Memory Poisoning · line 5
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
  • high Memory Poisoning · line 31
    Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.
    Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
  • high Tool Misuse · line 120
    Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).
    Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
  • high YARA Match · line 120
    YARA rule matched a known malware signature (reverse shell, backdoor, ransomware, C2 framework, or info stealer).
    Fix: Remove the malware payload or compromised file entirely. Investigate how it entered the skill and audit all other artifacts for additional indicators of compromise.
  • medium Excessive Agency · line 122
    Skill grants unrestricted tool access without appropriate constraints. An agent with unfettered tool access can perform arbitrary actions including file modification, network requests, and code execution.
    Fix: Restrict tool access to only the tools required for the skill's stated purpose. Use an explicit allowlist rather than granting blanket access.
  • medium Excessive Agency · line 214
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.04506
Opus 5.5 $0.00016 $0.01802
Sonnet 5.5 $0.00008 $0.00901
Haiku 4.5 $0.00004 $0.00451

Measured 9d ago against content hash 690e3b44f71d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

health scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 14 executable files (scripts/block-pipe-to-shell.py, scripts/check_agent_context.py, scripts/check_doc_refs.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/waza/skills/health/SKILL.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 evidence and risk, not repository size.

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: non-obvious constraint reachability, risk-backed hotspot ownership, verifier coverage, generated-artifact checks, and stale or misleading durable docs.

Output language: Follow the user's current language or explicit language request. Use applicable project and global defaults only when the request does not establish a language.

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, or when the summary pass exposes a critical ambiguity that cannot be resolved locally. Inventory counts never trigger escalation on their own. 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.

Read the full file on GitHub · 216 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago Changed 690e3b44f71d
  2. 14d ago Changed 7329b19ba208
  3. 17d ago Changed 197b7ddc2b5e
  4. 29d ago Changed b8141d48d51d
  5. 1mo ago Changed dbe6d99f930c
  6. 1mo ago Changed · +1 lines feba2d9551e3
  7. 1mo ago Changed · -31 tokens per session 364d997faa07
  8. 1mo ago Changed ddf50c9e2362
  9. 1mo ago Changed b3fd725bdde8
  10. 1mo ago First seen · 215 lines · 71 tokens per session scan A e504a761d9ba

Subscribe to this mod's changes

health is a skill published in the GitHub repository tw93/Waza (7,355 stars, last pushed today), licensed MIT. It adds 40 tokens to every session and 4,506 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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