Borrowing it
Nothing to install: this file belongs to shigechika/jquants-mcp. 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/shigechika/jquants-mcp/main/.claude/commands/review.mdgit clone --depth 1 https://github.com/shigechika/jquants-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/commands/shigechika/jquants-mcp/review)<a href="https://agentmods.dev/commands/shigechika/jquants-mcp/review"><img src="https://agentmods.dev/badge/commands/shigechika/jquants-mcp/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/commands/shigechika/jquants-mcp/review"><img src="https://agentmods.dev/badge/commands/shigechika/jquants-mcp/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 | $0.00008 | $0.00388 |
| Opus 5 | $0.00004 | $0.00194 |
| Sonnet 5 | $0.00002 | $0.00078 |
| Haiku 4.5 | $0.00001 | $0.00039 |
Grade A, and why
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 10d 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.
What it actually says
You are an expert code reviewer for the jquants-mcp repository. Always respond in Japanese (このプロジェクト全体での合意事項).
Follow these steps:
- If no PR number is provided in the args, run
gh pr listto show open PRs. - If a PR number is provided, run
gh pr view <number>to get PR details. - Run
gh pr diff <number>to get the diff. - Analyze the changes and provide a thorough code review in Japanese, with the following sections:
- 概要 (Overview) — what the PR does
- コード品質と style 分析 (Code quality / style)
- 改善提案 (Specific suggestions)
- 潜在的な問題 / リスク (Risks)
Keep your review concise but thorough. Focus on:
- Code correctness (正確性)
- Following project conventions (プロジェクト規約との整合性) — see
CLAUDE.md - Performance implications (パフォーマンス影響)
- Test coverage (テストカバレッジ)
- Security considerations (セキュリティ)
Format your review with clear section headers in Japanese and bullet points.
Tone:
- 技術的な事実と判断を分けて書く（"X is wrong" ではなく "X は仕様 Y に反します。理由は..."）。
- 英語の technical term（OAuth、AccessToken、claims、 cache.db 等）はそのまま使う。
- 日本語文中の括弧は全角
（）を優先（CLAUDE.md ルール）。 - 過剰な敬語は避けて簡潔に。
PR number: $ARGUMENTS
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.
- 10d ago First seen · 37 lines · 8 tokens per session scan A 6a53d24aab84
review is a command published in the GitHub repository shigechika/jquants-mcp (2 stars, last pushed 3d ago), licensed MIT. It adds 8 tokens to every session and 388 once invoked, about $0.0000 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.
Other commands, from other repositories
review-update-set
Review ServiceNow update sets — list sets by state, deep-review changes, compare sets, or run pre-promotion checks.
cleanup
Post-implementation quality gate that reviews changes, fixes small issues (scout rule), creates tasks for medium issues, and generates analysis for large issues.
speckit.verify-tasks
Verify tasks marked [X] in tasks.md are implemented, not phantom completions (marked done but backed by missing or dead code).
verify
Perform a non-destructive post-implementation verification gate validating the implementation against spec.md, plan.md, tasks.md, and constitution.md.
run
Comprehensive code review using specialized agents — orchestrates code, comments, tests, errors, types, and simplify agents sequentially.
types
Type design analysis — encapsulation, invariant expression, usefulness, and enforcement.