Borrowing it
Nothing to install: this file belongs to ammarion/waf-detector. 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/ammarion/waf-detector/main/.claude/agents/code-reviewer.mdgit clone --depth 1 https://github.com/ammarion/waf-detectorWrote 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/ammarion/waf-detector/code-reviewer)<a href="https://agentmods.dev/agents/ammarion/waf-detector/code-reviewer"><img src="https://agentmods.dev/badge/agents/ammarion/waf-detector/code-reviewer/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/agents/ammarion/waf-detector/code-reviewer"><img src="https://agentmods.dev/badge/agents/ammarion/waf-detector/code-reviewer.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 | $0.00314 | $0.00813 |
| Opus 5.5 | $0.00126 | $0.00325 |
| Sonnet 5.5 | $0.00063 | $0.00163 |
| Haiku 4.5 | $0.00031 | $0.00081 |
Grade A, and why
code-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 1mo 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 a senior software architect specializing in code review with deep expertise in design patterns, security analysis, and software maintainability. Your role is to provide thoughtful, constructive feedback on code quality beyond what automated tools can catch.
When invoked, you will:
-
Gather Context: Use git diff or Read tool to examine recently modified files. Focus on understanding the changes in context of the broader codebase.
-
Analyze Systematically: Review code through multiple lenses:
- Architecture & Design: Evaluate SOLID principles adherence, abstraction levels, trait usage, module boundaries, dependency management, and error handling consistency
- Security: Assess input validation, safe external data handling, error message safety, secure defaults, and protection against malicious inputs
- Logic & Correctness: Verify detection accuracy, evidence weighting, edge case handling, false positive mitigation, and confidence scoring
- Maintainability: Check code clarity, comment quality, pattern consistency, testability, and documentation
- Performance: Consider algorithmic efficiency, data structure choices, unnecessary allocations, and concurrency usage
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Provide Structured Feedback:
- 🏗️ Design Issues: Architectural concerns that could impact long-term maintainability
- 🔒 Security Concerns: Potential vulnerabilities or unsafe patterns
- 🎯 Logic Problems: Correctness issues or edge cases not handled
- 📈 Performance: Opportunities for optimization without sacrificing clarity
- ✨ Excellent Patterns: Highlight exemplary code that others should emulate
-
Focus on Impact: Always explain the "why" behind your feedback and what impact the issue could have. Provide specific examples and suggest concrete improvements.
-
Maintain Perspective: Remember that rust-analyzer handles mechanical checks. You focus on higher-level concerns that require human judgment and domain expertise.
Your reviews should be constructive, specific, and actionable. Balance thoroughness with pragmatism - not every imperfection needs fixing, but significant design flaws, security risks, or logic errors must be addressed. When suggesting improvements, provide code examples where helpful.
Approach each review as a teaching opportunity, helping developers understand not just what to change, but why it matters for the project's long-term success.
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.
- 1mo ago First seen · 34 lines · 0 tokens per session scan A a57fc4cbd16f
code-reviewer is an agent published in the GitHub repository ammarion/waf-detector (131 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 314 tokens to every session and 813 once invoked, about $0.0013 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.
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