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 commands/mturac/everything-openai-codex/fastapi-reviewgit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/mturac/everything-openai-codex/fastapi-review)<a href="https://agentmods.dev/commands/mturac/everything-openai-codex/fastapi-review"><img src="https://agentmods.dev/badge/commands/mturac/everything-openai-codex/fastapi-review.svg" alt="Measured on agentmods" 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 | $0.00027 | $0.00230 |
| Opus 5 | $0.00014 | $0.00115 |
| Sonnet 5 | $0.00005 | $0.00046 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
fastapi-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 2d 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.
This is a copy
100% identical to fastapi-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
FastAPI Review
Invoke the fastapi-reviewer agent for a focused FastAPI review.
Usage
/fastapi-review [file-or-directory]
Review Areas
- App factory, router boundaries, middleware, and exception handlers.
- Pydantic request and response schema separation.
- Dependency injection for database sessions, auth, pagination, and settings.
- Async database and external HTTP patterns.
- CORS, auth, rate limits, logging, and secret handling.
- OpenAPI metadata and documented response models.
- Test client setup and dependency overrides.
Expected Output
[SEVERITY] Short issue title
File: path/to/file.py:42
Issue: What is wrong and why it matters.
Fix: Concrete change to make.
Related
- Agent:
fastapi-reviewer - Skill:
fastapi-patterns - Command:
/python-review - Skill:
security-scan
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.
- 2d ago First seen · 40 lines · 27 tokens per session scan A 758f6c55befc
fastapi-review is a command published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 12d ago), licensed MIT. It adds 27 tokens to every session and 230 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to fastapi-review, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
fastapi-review
Review a FastAPI application for architecture, async correctness, dependency injection, Pydantic schemas, security, performance, and testability.
pn-audit-security
OWASP-guided security review — auth posture, input validation, secrets, CORS, JWT, rate limiting. Surgical command for backend security. Use standalone or as part of pn-backend-audit.
phase-review
阶段5：代码审查 — 通用审查 + 语言专项 + 安全审查（多模型交叉验证）.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.