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.
npx skills add jason21wc/ai-governance-mcp --skill code-reviewgit clone --depth 1 https://github.com/jason21wc/ai-governance-mcpWrote 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.
[](https://agentmods.dev/skills/jason21wc/ai-governance-mcp/code-review)<a href="https://agentmods.dev/skills/jason21wc/ai-governance-mcp/code-review"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/code-review/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.
<a href="https://agentmods.dev/skills/jason21wc/ai-governance-mcp/code-review"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.00818 |
| Opus 5.5 | $0.00040 | $0.00327 |
| Sonnet 5.5 | $0.00020 | $0.00164 |
| Haiku 4.5 | $0.00010 | $0.00082 |
Grade A, and why
code-review 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 2mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Runtime Context
After the skill loads, establish the branch and inspect staged and unstaged diffs with ordinary read-only Git calls. Distinguish a clean diff from a Git error.
Instructions
You are running a multi-pass code review. Read procedure.md in this skill folder for the full orchestration protocol.
Quick Start
-
Collect the Runtime Context above and determine review scope. If the user specified files or a diff range, use that. Otherwise:
- Staged changes exist → review staged changes (
git diff --cached) - On a branch other than main → review branch diff (
git diff main...HEAD) - Neither → ask the user what to review
- Staged changes exist → review staged changes (
-
Read
procedure.mdfor the full orchestration and reconciliation protocol. -
Read pass instruction files from
passes/directory. Each file contains focused review instructions for one subagent. -
Dispatch 3 Agent subagents in parallel — correctness, security, architecture. Each gets the shared assumptions brief + its pass-specific instructions.
-
Reconcile findings per the reconciliation protocol in procedure.md. Deduplicate, apply evidence gate, enforce severity gating and output cap.
-
Present the unified review in the output format defined in procedure.md.
Opt-In Passes
When the user says "full review", "include performance", or "include test coverage":
- Read additional pass files from
passes-optional/ - Dispatch additional subagents alongside the core 3
- Include their findings in reconciliation
Cross-vendor second opinion (passes-optional/cross-vendor.md) — an independent review
from a different model lineage (OpenAI Codex / gpt). Default where scripts/codex_review.py
exists in the repo AND codex is on PATH: run the security role automatically (promoted
from opt-in on the session-240 measurement — cheap, low-noise, caught a real miss). Elsewhere
it is opt-in: run when the user says "cross-vendor", "codex review", "second opinion", or
"full review". Unlike the other passes this is NOT a Claude subagent: the orchestrator runs it
via Bash (in parallel with the subagent dispatch) and folds its JSON findings into
reconciliation. It self-skips silently when codex is absent or the primary session is itself
Codex, so it is safe to leave on by default.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 63 lines · 99 tokens per session scan A 433c00994584
code-review is a skill published in the GitHub repository jason21wc/ai-governance-mcp (0 stars, last pushed 25d ago), licensed Apache-2.0. It adds 99 tokens to every session and 818 once invoked, about $0.0004 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 2026-08-31.
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