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 architecture-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/architecture-review)<a href="https://agentmods.dev/skills/jason21wc/ai-governance-mcp/architecture-review"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/architecture-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/architecture-review"><img src="https://agentmods.dev/badge/skills/jason21wc/ai-governance-mcp/architecture-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 | $0.00122 | $0.00836 |
| Opus 5.5 | $0.00049 | $0.00334 |
| Sonnet 5.5 | $0.00024 | $0.00167 |
| Haiku 4.5 | $0.00012 | $0.00084 |
Grade A, and why
architecture-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 — 56 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Runtime Context
After the skill loads, inspect the project root, top-level structure, representative file types, file count, and framework manifests with ordinary read-only calls. Derive the framework from the evidence; do not rely on eager injected output.
Instructions
You are performing a codebase architecture review. This skill answers: "How is this codebase organized, and is the architecture healthy?"
Read procedure.md in this skill folder for the full 3-phase protocol.
Quick Start
-
Collect the Runtime Context above and determine the scope. If the user specified a module or subsystem, focus there. If they said "review the architecture" without qualification, assess the entire codebase. If the codebase is very large (>500 files), recommend scoping to a subsystem.
-
Read
procedure.mdfor the full protocol. -
Execute all three phases in order:
- Phase 1: Map — module structure, entry points, dependency graph, layer identification
- Phase 2: Assess — layering integrity, cohesion, coupling hotspots, anti-patterns, growth capacity
- Phase 3: Report — structural map + health assessment + prioritized recommendations
-
Deliver the report with the structural map, health findings, and refactoring priorities.
Key Principles
- The structural map is the core deliverable. A dependency graph and module responsibility inventory that the user can reference for future decisions. Findings without the map are opinions; the map with findings is actionable intelligence.
- Tool-assisted mapping over manual reading. Use grep and import analysis to build the dependency graph. Manual code reading fills gaps but the skeleton comes from tooling.
- Honest about scope limitations. Grep finds imports and call sites, not runtime behavior. Dynamic dispatch, dependency injection, and event-driven patterns create invisible dependencies. Flag these as UNVERIFIED, same as
/refactor-auditdoes for invisible contracts. - Assessment, not prescription. Report what IS, evaluate its health, prioritize what to improve. Don't redesign the architecture — that's the user's job with this assessment as input.
What ships with it
1 file 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 · 56 lines · 122 tokens per session scan A 598836356e14
architecture-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 122 tokens to every session and 836 once invoked, about $0.0005 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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