Paste your CLAUDE.md or AGENTS.md and tell it what your agent actually did wrong. It names the rule that failed, quotes the line that should have caught it or says plainly that nothing in your file covers it, and hands you replacement text you can paste back. Built from logged incidents on a production pipeline run with a coding agent, not from general advice. With no incident it still reports what your file itself shows. It makes failures visible; it does not promise they stop.
Tell it your commands and gotchas, get a working AGENTS.md or CLAUDE.md back in the first reply. It captures fragile build steps, do-not-touch files, past mistakes and testing gotchas, marks gaps as TODOs and asks only what is missing. Ready for Claude Code, Cursor, Copilot and Codex.
List your recurring tasks; get a keep-as-agent / skill / script verdict and read-only .claude/agents drafts.
Audit AI agents, Skills, MCP configurations, tool permissions, and coding-agent setups for prompt injection, excessive agency, credential exposure, data leakage, unsafe code execution, supply-chain risks, memory risks, missing approval controls, and runaway autonomy. Get a calibrated Security Score, Audit Confidence, evidence-backed findings, remediation steps, verification checks, and residual-risk analysis.
Check whether your AI Agent tried to read, send, or use tools outside its approved scope before release. Get evidence, findings, fixes, and a clear release gate. Missing evidence may result in NOT_VERIFIED. General task correctness and complete safety are not guaranteed. Imported evidence is evaluated as supplied; trace authenticity is not independently attested.
Michelin-kitchen audit for your AI coding agent setup: finds where you are still the bottleneck, places you on the trust ladder, and hands you the one upgrade that lets you run more agents with less supervision.
This Skill is built on practical expertise in AI agent safety, prompt-injection defense, source-to-sink privacy review, tool and MCP metadata integrity, memory provenance checks, autonomous action scoping, and evidence-based verification. It helps agents separate instructions from evidence before tool calls, uploads, publishing, deletion, code execution, or network output.
Before you install an MCP server or agent skill, find out what it reads, runs, and sends. Share a GitHub URL or upload repository files to get an evidence-backed install decision, code citations, documentation mismatches, and targeted fixes. Also reviews coding-agent plugins. Static review; no code execution.