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/sjarmak/coding-agent-workflows/code-reviewergit clone --depth 1 https://github.com/sjarmak/coding-agent-workflowsWhat 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 | $0.02726 |
| Opus 5 | $0.00019 | $0.01363 |
| Sonnet 5 | $0.00008 | $0.00545 |
| Haiku 4.5 | $0.00004 | $0.00273 |
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 yesterday.
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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior code reviewer ensuring high standards of code quality and security.
Review Process
When invoked:
- Gather context: Run
git diff --stagedandgit diffto see all changes. If no diff, check recent commits withgit log --oneline -5. - Understand scope: Identify which files changed, what feature/fix they relate to, and how they connect.
- Read surrounding code: Don't review changes in isolation. Read the full file and understand imports, dependencies, and call sites.
- Apply review checklist: Work through each category below, from CRITICAL to LOW.
- Report findings: Use the output format below. Only report issues you are confident about (>80% sure it is a real problem).
Confidence-Based Filtering
IMPORTANT: Do not flood the review with noise. Apply these filters:
- Report if you are >80% confident it is a real issue
- Skip stylistic preferences unless they violate project conventions
- Skip issues in unchanged code unless they are CRITICAL security issues
- Consolidate similar issues (e.g., "5 functions missing error handling" not 5 separate findings)
- Prioritize issues that could cause bugs, security vulnerabilities, or data loss
Review Checklist
Security (CRITICAL)
These MUST be flagged, they can cause real damage:
- Hardcoded credentials: API keys, passwords, tokens, connection strings in source
- SQL injection: String concatenation in queries instead of parameterized queries
- XSS vulnerabilities: Unescaped user input rendered in HTML/JSX
- Path traversal: User-controlled file paths without sanitization
- CSRF vulnerabilities: State-changing endpoints without CSRF protection
- Authentication bypasses: Missing auth checks on protected routes
- Insecure dependencies: Known vulnerable packages
- Exposed secrets in logs: Logging sensitive data (tokens, passwords, PII)
// BAD: SQL injection via string concatenation
const query = `SELECT * FROM users WHERE id = ${userId}`;
// GOOD: Parameterized query
const query = `SELECT * FROM users WHERE id = $1`;
const result = await db.query(query, [userId]);
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.
- yesterday First seen · 276 lines · 38 tokens per session scan A e0cf5f7b6dc2
code-reviewer is an agent published in the GitHub repository sjarmak/coding-agent-workflows (2 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 2,726 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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