Borrowing it
Nothing to install: this file belongs to aoki-collabo/simple-hono-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aoki-collabo/simple-hono-mcp-server/main/.claude/commands/review-docs.mdgit clone --depth 1 https://github.com/aoki-collabo/simple-hono-mcp-serverWrote 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/commands/aoki-collabo/simple-hono-mcp-server/review-docs)<a href="https://agentmods.dev/commands/aoki-collabo/simple-hono-mcp-server/review-docs"><img src="https://agentmods.dev/badge/commands/aoki-collabo/simple-hono-mcp-server/review-docs.svg" alt="Measured on agentmods" 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 | $0.00017 | $0.00552 |
| Opus 5 | $0.00009 | $0.00276 |
| Sonnet 5 | $0.00003 | $0.00110 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
review-docs 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 5d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- review-docs — 100% identical, 0 lines differ
What it actually says
ドキュメントレビュー
引数: ドキュメントパス(例: /review-docs docs/product-requirements.md)
実行方法
claude
> /review-docs docs/product-requirements.md
手順
ステップ1: ドキュメントの存在確認
指定されたドキュメントが存在するか確認します。
ステップ2: doc-reviewerサブエージェント起動
doc-reviewerサブエージェントを起動してレビューを実行します:
Task toolを使用してdoc-reviewerサブエージェントを起動してください:
- subagent_type: "doc-reviewer"
- description: "Document detailed review"
- prompt: "[ドキュメントパス]を詳細にレビューしてください。\n\n以下の観点で評価してください:\n1. 完全性: 必要な項目が全て含まれているか\n2. 具体性: 曖昧な表現がないか\n3. 一貫性: 他のドキュメントと整合しているか\n4. 測定可能性: 成功指標が測定可能か(PRDの場合)\n\nレビューレポートを作成してください。"
ステップ3: レビュー結果の要約
サブエージェントが作成したレビューレポートの要点を抽出し、ユーザーに報告します。
出力形式
# ドキュメントレビュー結果
## ドキュメント: [ファイル名]
### 主な改善点
1. [改善点1] (優先度: 高/中/低)
2. [改善点2] (優先度: 高/中/低)
3. [改善点3] (優先度: 高/中/低)
### 総合評価
[1-5]/5
### 次のアクション
- [推奨対応1]
- [推奨対応2]
詳細なレポートはサブエージェントの出力を参照してください。
注意事項
- レビューは詳細な分析のため、数分かかる場合があります
- サブエージェントは独立したコンテキストで動作するため、メインエージェントのコンテキストは消費しません
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.
- 5d ago First seen · 63 lines · 17 tokens per session scan A f7fcb7ec33c8
review-docs is a command published in the GitHub repository aoki-collabo/simple-hono-mcp-server (1 stars, last pushed 7mo ago), licensed MIT. It adds 17 tokens to every session and 552 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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checklist
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.