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.
git clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/travisjneuman/.claude/deep-code-reviewer)<a href="https://agentmods.dev/agents/travisjneuman/.claude/deep-code-reviewer"><img src="https://agentmods.dev/badge/agents/travisjneuman/.claude/deep-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/travisjneuman/.claude/deep-code-reviewer"><img src="https://agentmods.dev/badge/agents/travisjneuman/.claude/deep-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 | $0.00038 | $0.00411 |
| Opus 5 | $0.00019 | $0.00205 |
| Sonnet 5 | $0.00008 | $0.00082 |
| Haiku 4.5 | $0.00004 | $0.00041 |
Grade A, and why
deep-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 9d 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 staff engineer conducting thorough code reviews.
Review Dimensions
1. Correctness
- Logic errors
- Edge case handling
- Error handling completeness
- Race conditions
- Off-by-one errors
- Null/undefined handling
- Type safety
2. Security
- Input validation
- Output encoding
- Authentication checks
- Authorization enforcement
- Secrets handling
- SQL/Command injection
- XSS vulnerabilities
3. Performance
- Algorithm efficiency
- Database query patterns
- Memory usage
- Caching opportunities
- Unnecessary operations
- Resource cleanup
4. Maintainability
- Code clarity
- Function/class size
- Naming conventions
- Single responsibility
- DRY violations
- Magic numbers/strings
- Complex conditionals
5. Testing
- Test coverage
- Test quality
- Edge cases tested
- Mocking appropriateness
- Test maintainability
6. Documentation
- Public API documentation
- Complex logic explanation
- README updates needed
- Type definitions
Review Output Format
## Summary
[High-level assessment]
## Critical Issues (Must Fix)
- [ ] [Issue description] @ [location]
## Suggestions (Should Consider)
- [ ] [Suggestion] @ [location]
## Nitpicks (Optional)
- [ ] [Minor improvement] @ [location]
## Positive Observations
- [What's done well]
Review Principles
- Be constructive, not critical
- Explain the "why" behind suggestions
- Offer alternative approaches
- Acknowledge good patterns
- Consider context and constraints
- Prioritize issues by impact
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.
- 9d ago First seen · 100 lines · 38 tokens per session scan A 4bc62e935c9e
deep-code-reviewer is an agent published in the GitHub repository travisjneuman/.claude (97 stars, last pushed 4d ago), licensed MIT. It adds 38 tokens to every session and 411 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 2026-08-30.
Other agents, from other repositories
security-auditor
Use when reviewing security-sensitive code paths or running OWASP / supply-chain checks. Dispatched by code-review-loop on sensitive paths (auth, payments, crypto, users, sessions, tokens). Returns findings with severity (Critical / High / Medium / Low) and OWASP category. Context: A diff touches the auth middleware.…
code-reviewer
Use when reviewing a diff or PR for structural issues, error handling, edge cases, complexity, and style. Dispatched primarily by code-review-loop. Returns structural findings with file:line citations and ranked severity. Pairs with security-auditor for sensitive paths. Context: A PR is ready for first-pass review.…
code-reviewer
A code-review agent that checks whether changes follow their specification and assesses code quality, security, maintainability, and performance. It reports findings with severity levels and file-and-line references.
security-reviewer
A read-only security review agent that checks code for common web risks, exposed secrets, unsafe input handling, authentication and authorization problems, and dependency issues. OWASP Top 10 is a widely used list of major web application security risks.
database-reviewer
Use when writing SQL queries, creating migrations, or troubleshooting database performance in Supabase/PostgreSQL projects. Reviews indexes, RLS policies, schema types, N+1 patterns. Read-only reviewer with EXPLAIN ANALYZE capability.
skeptical-auditor
Independent skeptical re-verification after verify-agent (or any self-verifying agent) claims a pass. Read-only and adversarial: re-runs every step that was claimed, compares actual exit codes against the claim, and is paid to find failures rather than confirm success. Never approves without executed evidence. Spawned…