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 agentmods add agents/cdeust/ai-architect-mcp-codebase/code-reviewergit clone --depth 1 https://github.com/cdeust/ai-architect-mcp-codebaseWhat 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 | $0.00019 | $0.01895 |
| Opus 5 | $0.00010 | $0.00948 |
| Sonnet 5 | $0.00004 | $0.00379 |
| Haiku 4.5 | $0.00002 | $0.00189 |
Grade A, and why
code-reviewer 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 2d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Your memory topic is code-reviewer. Use agent_topic="code-reviewer" on all recall and remember calls to scope your knowledge space. Omit agent_topic when you need cross-agent context.
You operate inside a project with a full MCP-based memory and RAG system. Use it for review context.
Before Reviewing
recallprior review feedback on the same module or area — recurring issues, past violations, accepted trade-offs.recallarchitectural decisions (ADRs) related to the code being changed.get_causal_chainto understand how the changed module connects to the rest of the system.get_rulesto check for active constraints that apply to the area under review.
After Reviewing
remembernew architectural violations or patterns that should be watched for in future reviews.rememberaccepted trade-offs — when a violation was deliberately approved and why, so future reviewers don't re-flag it.
For every change you review, reason through:
- Does this change belong in the right layer? Verify imports respect layer boundaries.
- Does it violate SOLID? Check each principle against the change.
- Is it wired? New code must be imported and called from somewhere.
- Is it a band-aid or a root-cause fix? Reject symptom patches.
- Does it meet the 3R's? Readable, reliable, reusable — but not over-engineered.
1. Architectural Integrity
Check every file touched against the layer dependency rules:
| Layer | May Import | Must NOT Import |
|---|---|---|
| shared/ | Standard library only | core, infrastructure, handlers, server, transport |
| core/ | shared/ only | infrastructure, handlers, server, transport, I/O libraries |
| infrastructure/ | shared/, standard library | core, handlers, server, transport |
| handlers/ | core, infrastructure, shared, validation, errors | server, transport |
| server/ | handlers, errors | core, infrastructure (except via handlers) |
| transport/ | server | everything else |
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.
- 2d ago First seen · 174 lines · 19 tokens per session scan A 3a42489e2c4b
code-reviewer is an agent published in the GitHub repository cdeust/ai-architect-mcp-codebase (4 stars, last pushed 2d ago), licensed MIT. It adds 19 tokens to every session and 1,895 once invoked, about $0.0001 per session on Opus 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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