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 skills/florianbruniaux/claude-code-plugins/review-plannpx skills add FlorianBruniaux/claude-code-plugins --skill review-plangit clone --depth 1 https://github.com/FlorianBruniaux/claude-code-pluginsWrote 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/florianbruniaux/claude-code-plugins/review-plan)<a href="https://agentmods.dev/skills/florianbruniaux/claude-code-plugins/review-plan"><img src="https://agentmods.dev/badge/skills/florianbruniaux/claude-code-plugins/review-plan.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 | $0.00024 | $0.00761 |
| Opus 5 | $0.00012 | $0.00380 |
| Sonnet 5 | $0.00005 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
review-plan 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 yesterday.
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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Plan Before Implementation
Review the current plan thoroughly before making any code changes. For every issue or recommendation, explain the concrete tradeoffs, give an opinionated recommendation, and ask for user input before assuming a direction.
Engineering Preferences
Use these to guide your recommendations (override with project-specific CLAUDE.md preferences if they exist):
- DRY is important: flag repetition aggressively
- Well-tested code is non-negotiable: prefer too many tests over too few
- Code should be "engineered enough": not under-engineered (fragile, hacky) and not over-engineered (premature abstraction, unnecessary complexity)
- Err on the side of handling more edge cases, not fewer
- Bias toward explicit over clever; thoughtfulness over speed
Review Pipeline
Work through each section sequentially. After each section, pause and ask for feedback before moving on.
1. Architecture Review
Evaluate:
- Overall system design and component boundaries
- Dependency graph and coupling concerns
- Data flow patterns and potential bottlenecks
- Scaling characteristics and single points of failure
- Security architecture (auth, data access, API boundaries)
2. Code Quality Review
Evaluate:
- Code organization and module structure
- DRY violations (be aggressive here)
- Error handling patterns and missing edge cases (call these out explicitly)
- Technical debt hotspots
- Areas that are over-engineered or under-engineered relative to engineering preferences
3. Test Review
Evaluate:
- Test coverage gaps (unit, integration, e2e)
- Test quality and assertion strength
- Missing edge case coverage (be thorough)
- Untested failure modes and error paths
4. Performance Review
Evaluate:
- N+1 queries and database access patterns
- Memory-usage concerns
- Caching opportunities
- Slow or high-complexity code paths
Issue Reporting Format
For every specific issue found (bug, smell, design concern, or risk):
- Describe the problem concretely, with file and line references
- Present 2-3 options, including "do nothing" where that's reasonable
- For each option, specify: implementation effort, risk, impact on other code, and maintenance burden
- Give your recommended option and why, mapped to engineering preferences above
- Ask explicitly whether the user agrees or wants to choose a different direction before proceeding
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.
- yesterday First seen · 97 lines · 24 tokens per session scan A 1904c3f83a7c
review-plan is a skill published in the GitHub repository FlorianBruniaux/claude-code-plugins (40 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 761 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 2026-09-04.
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code-review
代码审查，从需求符合度/正确性/安全性/可维护性/性能五维度评审代码变更，输出风险分级的 Finding 列表.
technical-design
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audit
审计最近一段时间的自动维护活动（events / proposals / decay / digest），给用户汇总报告.