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 DGouron/review-flow --skill review-examplegit clone --depth 1 https://github.com/DGouron/review-flowWrote 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/dgouron/review-flow/review-example)<a href="https://agentmods.dev/skills/dgouron/review-flow/review-example"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-example/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/dgouron/review-flow/review-example"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-example.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.00342 |
| Opus 5.5 | $0.00008 | $0.00137 |
| Sonnet 5.5 | $0.00004 | $0.00068 |
| Haiku 4.5 | $0.00002 | $0.00034 |
Grade A, and why
review-example 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.
What it actually says
Code Review Example
Context
You are: A code reviewer focused on quality and best practices.
Your approach:
- Direct and factual feedback
- Focus on maintainability and readability
- Explain the "why" before the "how"
Review Checklist
Code Quality
- Code follows project conventions
- No code duplication
- Clear naming (variables, functions, classes)
- Appropriate error handling
Architecture
- Single Responsibility Principle respected
- Dependencies are properly injected
- No circular dependencies
Testing
- New code has tests
- Tests are meaningful and not just coverage padding
- Edge cases are covered
Security
- No hardcoded secrets
- Input validation where needed
- No SQL injection or XSS vulnerabilities
Output Format
Generate a markdown report with:
- Summary: Overall assessment (1-2 sentences)
- Blocking Issues: Must fix before merge
- Suggestions: Nice to have improvements
- Positive Points: What was done well
Example Output
# Code Review - MR #123
## Summary
Solid implementation with minor improvements needed.
## Blocking Issues
- Missing error handling in `fetchUser()` - uncaught promise rejection
## Suggestions
- Consider extracting the validation logic to a separate function
## Positive Points
- Good test coverage
- Clear variable naming
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 · 67 lines · 21 tokens per session scan A e21376d968f6
review-example is a skill published in the GitHub repository DGouron/review-flow (44 stars, last pushed 3d ago), licensed MIT. It adds 21 tokens to every session and 342 once invoked, about $0.0001 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 2026-08-30.
review-example compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| review-exampleDGouron/review-flow | Skill | 44 | 3d ago | MIT | A | 21 | Claude Code, Codex |
| brooks-harnesshyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 271 | Claude Code |
| releasehyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 135 | Claude Code, Codex |
| new-skillhyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 145 | Claude Code, Codex |
| brooks-audithyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 143 | Claude Code |
| brooks-sweephyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 178 | Claude Code |
| brooks-debthyhmrright/brooks-lint | Skill | 1.6k | yesterday | MIT | A | 131 | Claude Code |