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Yao Doctor Skill

DevOps & Security
yao-doctor-skill

Yao Doctor Skill is an Agent Skill for devops & security published in the yaojingang/yao-open-skills repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.

Audit local and OpenClaw skill libraries for privacy theft, credential theft, stealthy exfiltration, unsafe execution chains, deceptive instructions, and persistence behavior, then generate a visual HTML security report. Use when Codex needs to security-review one skill or a full skill library before install, enablement, or execution. Do not use for generic cleanup, usage estimation, or app-level security review outside skill packages.

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QUICK START

How to use this skill

Bring this guide into your coding agent with a prompt tailored to the tool you use.

  1. Open your project in Codex.
  2. Copy and paste the prompt below.
  3. Review files and risks before approving any action.
Prompt to paste
Inspect the Agent Skill at https://github.com/yaojingang/yao-open-skills/blob/HEAD/skills/yao-doctor-skill/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/yao-doctor-skill, but wait for my approval before writing files or running scripts.

Copying this prompt does not install or run the skill. Review third-party files before use.

Yao Doctor Skill

Boundary

Own this recurring job: security-review skill packages as untrusted code and untrusted instructions, separate broad capability risk from actual unsafe behavior, and produce evidence-backed recommendations before the skills are installed or executed.

Do not route here for:

  • generic code security reviews outside skill folders
  • skill cleanup, archival, deduplication, or stale-usage analysis
  • privacy policy writing without scanning files
  • creating a brand-new skill with no security audit need

Default Workflow

  1. Run scripts/run_yao_doctor_skill.py [root] [more-roots]. If no roots are provided, auto-discover the current workspace, OpenClaw skill roots, Codex and Claude local skill roots, Codex plugin-cache skills, supported local workbench configuration surfaces, and project-level workbench surfaces such as repo AGENTS.md, CLAUDE.md, or selected .claude/.codex files.
  2. Scan every discovered skill directory containing SKILL.md, plus recognized workbench surfaces such as local Codex and Claude configuration bundles and project-local agent configuration areas.
  3. For each skill, score two separate layers:
    • capability risk: what the skill can access or execute
    • unsafe behavior: what the skill appears to do with sensitive data or hidden actions
  4. Reuse the incremental cache when possible, and surface per-target diffs plus evidence type and confidence in the final report.
  5. Generate _yao_doctor_skill_reports/<timestamp>/report.html, report.json, and report.md. Also update the stable entry:
    • full scans -> _yao_doctor_skill_reports/full-library-latest/report.html
    • changed-only scans -> _yao_doctor_skill_reports/changed-only-latest/report.html
  6. Summarize the highest-severity findings first, with exact paths, lines, evidence type, confidence, and the reason a finding is merely risky, suspicious, unsafe, or critical.

Security Principles

  • Do not equate broad permissions with automatic compromise.
  • Treat a skill as unsafe only when there is evidence of privacy theft, credential theft, stealthy exfiltration, deceptive behavior, remote execution, or persistence abuse.
  • Distinguish capability from intent. A skill may be powerful without being malicious.
  • Escalate hard when a sensitive source and an external sink appear in the same execution path or file.
  • Favor precise path-level evidence over generic suspicion.
  • Stay read-only unless the user explicitly authorizes destructive or quarantine actions.

Outputs

Primary artifact:

  • visual HTML security report with the fixed section order:
    • overview
    • data analysis
    • definitions
    • module guide
    • skill modules
    • footer credit

Current interactive contract:

  • sticky top navigation
  • Chinese default with English toggle
  • linked type filters between data analysis and module list
  • module cards with audit opinion, findings, and capability evidence
  • stable latest report entry for in-app browsing and reuse

Per skill, include:

  • absolute path
  • declared skill name and one-line summary
  • capability risk score and level
  • unsafe behavior score and level
  • final disposition: safe, risky, suspicious, unsafe, or critical
  • top capabilities discovered
  • concrete findings with file path, line, category, severity, rationale, and recommended action

Resources