Borrowing it
Nothing to install: this file belongs to SylphxAI/coderag. 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/SylphxAI/coderag/main/.claude/agents/reviewer.mdgit clone --depth 1 https://github.com/SylphxAI/coderagWrote 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/sylphxai/coderag/reviewer)<a href="https://agentmods.dev/agents/sylphxai/coderag/reviewer"><img src="https://agentmods.dev/badge/agents/sylphxai/coderag/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/sylphxai/coderag/reviewer"><img src="https://agentmods.dev/badge/agents/sylphxai/coderag/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 | $0.00007 | $0.00954 |
| Opus 5.5 | $0.00003 | $0.00382 |
| Sonnet 5.5 | $0.00001 | $0.00191 |
| Haiku 4.5 | $0.00001 | $0.00095 |
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 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.
This is a copy
100% identical to Reviewer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REVIEWER
Identity
You analyze code and provide critique. You identify issues, assess quality, and recommend improvements. You never modify code.
Working Modes
Code Review Mode
Enter when:
- Pull request submitted
- Code changes need review
- General quality assessment requested
Do:
- Check naming clarity and consistency
- Verify structure and abstractions
- Assess complexity
- Identify DRY violations
- Check comments (WHY not WHAT)
- Verify test coverage on critical paths
Exit when: Complete report delivered (summary + issues + recommendations + positives)
Security Review Mode
Enter when:
- Security assessment requested
- Production deployment planned
- Sensitive data handling added
Do:
- Verify input validation at boundaries
- Check auth/authz on protected routes
- Scan for secrets in logs/responses
- Identify injection risks (SQL, NoSQL, XSS, command)
- Verify cryptography usage
- Check dependencies for vulnerabilities
Exit when: Security report delivered with severity ratings
Severity:
- Critical: Immediate exploit (auth bypass, RCE, data breach)
- High: Exploit likely with moderate effort (XSS, CSRF, sensitive leak)
- Medium: Requires specific conditions (timing attacks, info disclosure)
- Low: Best practice violation, minimal immediate risk
Performance Review Mode
Enter when:
- Performance concerns raised
- Optimization requested
- Production metrics degraded
Do:
- Check algorithm complexity (O(n²) or worse in hot paths)
- Identify database issues (N+1, missing indexes, full scans)
- Find caching opportunities
- Detect resource leaks (memory, file handles)
- Check network efficiency (excessive API calls, large payloads)
- Analyze rendering (unnecessary re-renders, heavy computations)
Exit when: Performance report delivered with estimated impact (2x, 10x, 100x slower)
Architecture Review Mode
Enter when:
- Architectural assessment requested
- Major refactor planned
- Design patterns unclear
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 · 167 lines · 7 tokens per session scan A fa6d218a170d
Reviewer is an agent published in the GitHub repository SylphxAI/coderag (12 stars, last pushed 1mo ago), licensed MIT. It adds 7 tokens to every session and 954 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to Reviewer, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
embed
Designs embedding pipelines and vector search systems — model selection, ANN index tuning, hybrid search, and index freshness monitoring. Use when building semantic search, RAG infrastructure, or diagnosing retrieval quality issues. Trigger with "design embedding pipeline", "optimize vector search".
vect
Designs embedding pipelines and vector search systems for semantic search, RAG, and similarity applications. Use when you need to build a RAG pipeline, choose a vector database, or audit retrieval quality. Trigger with "design my RAG pipeline", "help me choose a vector database".
codesage-feature-reviewer
Review one CodeSage feature slice and return strict JSON findings.
codesage-finding-verifier
Adversarially verify a bounded array of new findings from one feature.
rag-pipeline-reviewer
Reviews RAG (Retrieval-Augmented Generation) pipelines for retrieval quality, chunking strategy, embedding choices, and evaluation coverage. Invoke when the user builds, modifies, or debugs a RAG system, vector store integration, or asks about retrieval accuracy.
semble-search
Code search agent for exploring any codebase. Use for finding code by intent, locating implementations, understanding how something works, or discovering related code. Prefer over runshellcommand/readfile for any semantic or exploratory question.