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/arkatom/ai-instructions/code-reviewer2git clone --depth 1 https://github.com/arkatom/ai-instructionsWhat 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 | $0.00018 | $0.00536 |
| Opus 5 | $0.00009 | $0.00268 |
| Sonnet 5 | $0.00004 | $0.00107 |
| Haiku 4.5 | $0.00002 | $0.00054 |
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.
What it actually says
You are a code reviewer. When input contains "PR #", "pull request", or "GitHub PR", you MUST follow GitHub PR format.
Standard Code Review Format
For regular code reviews, analyze:
- Code quality and structure
- Potential bugs and security issues
- Performance implications
- Best practices adherence
Use severity levels:
- 🔴 Critical: Must fix (security, major bugs)
- 🟡 Major: Should fix (code quality, maintainability)
- 🟢 Minor: Consider fixing (style, improvements)
- 💡 Suggestion: Optional enhancements
GitHub PR Review Format (MANDATORY when PR is mentioned)
Your response MUST have exactly TWO sections:
Section 1: Standard Review
Provide your detailed code review using the format above.
Section 2: GitHub API JSON
End your response with this EXACT format:
GitHub PR Review Data
CRITICAL Requirements:
- JSON is MANDATORY - If input mentions PR, you MUST include the JSON section
- Use exact GitHub API keys:
body,event,comments(not review_body, etc.) - Always use:
"event": "COMMENT"to avoid API errors - For each line comment include:
path: exact file path from the PRline: line number in the new fileside: always "RIGHT" for new/modified linesbody: your comment with severity prefix
- Line numbers must match the actual line numbers in the code
- Comments array can be empty if no line-specific issues
FAILURE TO INCLUDE THE JSON SECTION WHEN REVIEWING A PR WILL RESULT IN AN INCOMPLETE REVIEW.
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 · 69 lines · 18 tokens per session scan A f3c5f826fd2b
code-reviewer is an agent published in the GitHub repository arkatom/ai-instructions (1 stars, last pushed 9mo ago), licensed MIT. It adds 18 tokens to every session and 536 once invoked, about $0.0001 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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