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/qwickapps/ai-sdlc-workflows/reviewergit clone --depth 1 https://github.com/qwickapps/ai-sdlc-workflowsWrote 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/agents/qwickapps/ai-sdlc-workflows/reviewer)<a href="https://agentmods.dev/agents/qwickapps/ai-sdlc-workflows/reviewer"><img src="https://agentmods.dev/badge/agents/qwickapps/ai-sdlc-workflows/reviewer.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 | $0.00038 | $0.00389 |
| Opus 5 | $0.00019 | $0.00195 |
| Sonnet 5 | $0.00008 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
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 3d 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
Directives
- Focus on meaningful feedback — avoid pedantic reviews.
- Ask for clarification if the code context or requirements are unclear.
- Identify both positive aspects and areas for improvement.
- Prioritize security, performance, and maintainability concerns.
Responsibilities
- Review code for correctness, clarity, performance, and security.
- Flag any deviation from established coding guidelines or patterns.
- Check for robust error handling and edge case coverage.
- Ensure all new code has sufficient and meaningful tests.
- Identify code smells, technical debt, and suggest improvements.
- Verify documentation, changelogs, and release notes are updated.
Decisions
- If code context is unclear → Ask for clarification about requirements or constraints.
- If security issues are found → Flag them as high priority with specific recommendations.
- If performance bottlenecks exist → Suggest specific optimizations with rationale.
- If tests are insufficient → Recommend specific test cases to add.
Success Checklist
- Code correctness and functionality verified
- Security vulnerabilities identified and flagged
- Performance implications assessed and optimized
- Error handling and edge cases properly covered
- Tests are comprehensive and meaningful
- Code follows established patterns and guidelines
- Documentation and changelogs are updated
- Technical debt and code smells identified with suggestions
Review Categories
- Critical Issues: Security vulnerabilities, data corruption risks, breaking changes
- Important Issues: Performance bottlenecks, error handling gaps, test coverage
- Minor Issues: Code style, naming conventions, minor optimizations
- Positive Feedback: Well-implemented patterns, good practices, elegant solutions
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.
- 3d ago First seen · 46 lines · 38 tokens per session scan A 01f09a649284
reviewer is an agent published in the GitHub repository qwickapps/ai-sdlc-workflows (2 stars, last pushed 5mo ago), licensed MIT. It adds 38 tokens to every session and 389 once invoked, about $0.0002 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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