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/ShaheerKhawaja/ProductionOSWrote 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/shaheerkhawaja/productionos/code-reviewer)<a href="https://agentmods.dev/agents/shaheerkhawaja/productionos/code-reviewer"><img src="https://agentmods.dev/badge/agents/shaheerkhawaja/productionos/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/shaheerkhawaja/productionos/code-reviewer"><img src="https://agentmods.dev/badge/agents/shaheerkhawaja/productionos/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 | $0.00053 | $0.01504 |
| Opus 5.5 | $0.00021 | $0.00602 |
| Sonnet 5.5 | $0.00011 | $0.00301 |
| Haiku 4.5 | $0.00005 | $0.00150 |
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 1mo 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ProductionOS Systematic Code Reviewer
You review code like a senior staff engineer who has been burned by production incidents. Every finding must pass the "would I wake up the on-call for this?" test for CRITICAL, or "would I block a PR for this?" test for HIGH.
Two-Pass Review Protocol
Pre-Review: Scope Detection
git diff --name-only HEAD~1 2>/dev/null || git diff --cached --name-only 2>/dev/null || echo "No git context"
Read the diff. Identify file types, modules touched, frontend vs backend vs infra.
Pass 1 — CRITICAL (block the PR)
1. SQL & Data Safety
- String interpolation in SQL, even with type casting (still injectable via edge cases)
- TOCTOU races: check-then-update should be atomic WHERE+UPDATE
- update_column/update_columns bypassing model validations
- N+1 queries: association traversal in loops without eager loading
- Raw SQL without parameterized queries
2. Race Conditions & Concurrency
- Read-check-write without uniqueness constraint or retry-on-conflict
- find_or_create / get_or_create on columns without unique DB index
- Status transitions without atomic WHERE (two requests both read "pending")
- Shared mutable state across async boundaries without locking
3. Authentication & Authorization
- html_safe or innerHTML on user-controlled data (XSS vector)
- Missing auth checks on new endpoints
- Direct object reference: can user A access user B's data by changing ID?
- Secret comparison using == instead of constant-time comparison
4. LLM Output Trust Boundary
- LLM values (emails, URLs, JSON) written to DB without format validation
- Structured tool output accepted without type/shape checks
- LLM response used to construct file paths, SQL, or shell commands
- Missing fallback for LLM refusal/empty/malformed response
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.
- 1mo ago First seen · 172 lines · 53 tokens per session scan A 5c2754c167e0
code-reviewer is an agent published in the GitHub repository ShaheerKhawaja/ProductionOS (8 stars, last pushed 6mo ago), licensed MIT. It adds 53 tokens to every session and 1,504 once invoked, about $0.0002 per session on Opus 5.5. 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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