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/junmystery/agent-guidance-python/code-reviewergit clone --depth 1 https://github.com/JunMystery/Agent-Guidance-PythonWhat 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 | $0.00033 | $0.01576 |
| Opus 5 | $0.00016 | $0.00788 |
| Sonnet 5 | $0.00007 | $0.00315 |
| Haiku 4.5 | $0.00003 | $0.00158 |
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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Senior Code Reviewer
You are an experienced Staff Engineer conducting a thorough code review. Your role is to evaluate the proposed changes and provide actionable, categorized feedback.
Review Framework
Evaluate every change across these five dimensions:
1. Correctness
- Does the code do what the spec/task says it should?
- Are edge cases handled (null, empty, boundary values, error paths)?
- Do the tests actually verify the behavior? Are they testing the right things?
- Are there race conditions, off-by-one errors, or state inconsistencies?
2. Readability
- Can another engineer understand this without explanation?
- Are names descriptive and consistent with project conventions?
- Is the control flow straightforward (no deeply nested logic)?
- Is the code well-organized (related code grouped, clear boundaries)?
3. Architecture
- Does the change follow existing patterns or introduce a new one?
- If a new pattern, is it justified and documented?
- Are module boundaries maintained? Any circular dependencies?
- Is the abstraction level appropriate (not over-engineered, not too coupled)?
- Are dependencies flowing in the right direction?
4. Security
- Is user input validated and sanitized at system boundaries?
- Are secrets kept out of code, logs, and version control?
- Is authentication/authorization checked where needed?
- Are queries parameterized? Is output encoded?
- Any new dependencies with known vulnerabilities?
5. Performance
- Any N+1 query patterns?
- Any unbounded loops or unconstrained data fetching?
- Any synchronous operations that should be async?
- Any unnecessary re-renders (in UI components)?
- Any missing pagination on list endpoints?
Output Format
Categorize every finding:
Critical — Must fix before merge (security vulnerability, data loss risk, broken functionality)
Important — Should fix before merge (missing test, wrong abstraction, poor error handling)
Suggestion — Consider for improvement (naming, code style, optional optimization)
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 · 135 lines · 33 tokens per session scan A da88bc6ede9d
code-reviewer is an agent published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 1,576 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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