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/commands/shaheerkhawaja/productionos/review)<a href="https://agentmods.dev/commands/shaheerkhawaja/productionos/review"><img src="https://agentmods.dev/badge/commands/shaheerkhawaja/productionos/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/commands/shaheerkhawaja/productionos/review"><img src="https://agentmods.dev/badge/commands/shaheerkhawaja/productionos/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 | $0.00033 | $0.00578 |
| Opus 5 | $0.00016 | $0.00289 |
| Sonnet 5 | $0.00007 | $0.00116 |
| Haiku 4.5 | $0.00003 | $0.00058 |
Grade A, and why
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 10d 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/review — Pre-Landing Code Review
Analyze the current diff with the rigor of a principal engineer on a critical PR.
Step 0: Preamble
Run templates/PREAMBLE.md. Detect base branch.
Step 1: Gather Context
git diff --stat $(git merge-base HEAD origin/main)..HEAD
git log --oneline $(git merge-base HEAD origin/main)..HEAD
Step 2: Review Checklist
SQL Safety
- No string interpolation in SQL queries
- All user input parameterized
- LIKE patterns escaped (escape_like utility)
- No SELECT * in production code
- Migrations are reversible
LLM Trust Boundaries
- LLM output is never used in SQL, shell commands, or code execution
- User-provided prompts are sanitized
- LLM responses are validated before acting on them
- Token limits enforced on inputs
Conditional Side Effects
- No side effects in if-condition evaluation
- No mutations in logging statements
- No network calls in property getters
- No database writes in validation logic
Security
- No secrets in code (API keys, tokens, passwords)
- Auth checks on every endpoint
- CSRF protection on state-changing operations
- Input validation at system boundaries
Tests
- New code has corresponding tests
- Edge cases covered (empty, null, boundary values)
- Error paths tested
- No tests disabled or skipped without explanation
Dependencies
- New deps justified and maintained
- No known CVEs in added packages
- License compatible
Step 3: Findings
For each issue found:
### REVIEW-NNN: [CRITICAL|HIGH|MEDIUM|LOW] — {description}
**File:** {path}:{line}
**Evidence:** {code snippet}
**Fix:** {specific remediation}
Agent References
- Dispatch
code-reviewerfor deep code analysis - Dispatch
vulnerability-explorerfor security focus - Dispatch
adversarial-reviewerfor attack surface analysis
Self-Eval
Run templates/SELF-EVAL-PROTOCOL.md. Was every file in the diff reviewed? Were findings evidence-based?
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.
- 10d ago First seen · 78 lines · 33 tokens per session scan A 6289ab58a0a3
review is a command published in the GitHub repository ShaheerKhawaja/ProductionOS (8 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 578 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.
Other commands, from other repositories
red-book
Use after receiving PR review feedback. Extracts conventions from reviewer comments and offers to add them to CLAUDE.md. Closes the convention learning loop.
audit
Audit an existing codebase. Detects stack, finds gaps, creates tasks, generates PROJECT.md.
release
Release manager for frontend and mobile. Writes App Store notes, user-facing changelog, flags stale docs and landing copy. Actions: notes | changelog | docs | sync.
rfc
RFC process for cross-team decisions. Create, track, and close RFCs. Accepted RFCs auto-create ADRs.
discover
Run a full product discovery cycle — from outcome definition through opportunity mapping, prioritisation, and experiment design. Use when the team isn't sure what to build next, or before writing a PRD for a complex feature space.
migrate
Migrate existing PROJECT.md to the latest greatcto schema — appends missing fields without touching existing values.