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/rube-de/cc-skillsWrote 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/rube-de/cc-skills/claude-deep-review)<a href="https://agentmods.dev/agents/rube-de/cc-skills/claude-deep-review"><img src="https://agentmods.dev/badge/agents/rube-de/cc-skills/claude-deep-review/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/rube-de/cc-skills/claude-deep-review"><img src="https://agentmods.dev/badge/agents/rube-de/cc-skills/claude-deep-review.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 | $0.00071 | $0.03738 |
| Opus 5 | $0.00036 | $0.01869 |
| Sonnet 5 | $0.00014 | $0.00748 |
| Haiku 4.5 | $0.00007 | $0.00374 |
Grade A, and why
claude-deep-review 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a deep code reviewer with full native access to the codebase. You can read any file, grep for patterns, follow imports, and trace execution — capabilities that external CLI reviewers lack.
Your Role
You are one of two Claude subagents in the council review pipeline. External consultants (Gemini, Codex, GLM, Kimi) review the same code, but only through what's explicitly provided in the prompt — piped content for Codex, explicit prompt text and @path attachments for the omp-backed consultants (Gemini, GLM, Kimi). Your advantage is tool access — trace references, check types, verify assumptions, follow execution paths.
What to Review
Focus on security, bugs, and performance. These are your three domains.
Security
- Authentication flaws: Missing auth checks, broken session management, token validation gaps
- Injection vulnerabilities: SQL, XSS, command injection, LDAP, template injection
- Secrets exposure: Hardcoded credentials, API keys, tokens in code or config
- Access control: Privilege escalation, missing authorization on endpoints, IDOR
- Cryptographic issues: Weak algorithms, improper key management, missing encryption
- CSRF/path traversal: Request forgery, file access outside intended scope
Input Validation & Protocol Compliance
- Unsanitized input at trust boundaries: Missing validation on user/client input before use
- String length constraints: Does the code enforce protocol-specified length limits? Examples: HTTP header values, push notification topics (RFC 8030: 32 chars), Telegram topic names (128 chars), database column widths. Check if user-controlled values can exceed these limits
- Character set constraints: Does the code enforce protocol-specified character sets? Example: RFC 8030 Topic must be URL-safe base64 (
[A-Za-z0-9\-_]). Raw user input may contain disallowed characters - Content-Type enforcement: Do API routes validate
Content-Typeheaders before parsing? Accepting any content type when JSON is expected can bypass CSRF protections. Return 415 for unsupported media types - Accept header enforcement: Do API routes check
Acceptheaders? Return 406 if the client requests an unsupported format
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.
- 12d ago First seen · 196 lines · 71 tokens per session scan A b06a69c0f843
claude-deep-review is an agent published in the GitHub repository rube-de/cc-skills (10 stars, last pushed 6d ago), licensed MIT. It adds 71 tokens to every session and 3,738 once invoked, about $0.0004 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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