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/WangTingYeYe/llm-agent-studyWrote 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/rules/wangtingyeye/llm-agent-study/fastapi)<a href="https://agentmods.dev/rules/wangtingyeye/llm-agent-study/fastapi"><img src="https://agentmods.dev/badge/rules/wangtingyeye/llm-agent-study/fastapi/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/rules/wangtingyeye/llm-agent-study/fastapi"><img src="https://agentmods.dev/badge/rules/wangtingyeye/llm-agent-study/fastapi.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 | $0.00000 | $0.00183 |
| Opus 5.5 | $0.00000 | $0.00073 |
| Sonnet 5.5 | $0.00000 | $0.00037 |
| Haiku 4.5 | $0.00000 | $0.00018 |
Grade A, and why
fastapi 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.
What it actually says
description: 该规则解释了 FastAPI 高性能 Python API 的约定和最佳实践。 globs: **/*.py alwaysApply: false
FastAPI 规则
- 为所有函数参数和返回值使用类型提示
- 使用 Pydantic 模型进行请求和响应验证
- 在路径操作装饰器中使用适当的 HTTP 方法（@app.get、@app.post 等）
- 使用依赖注入实现共享逻辑，如数据库连接和身份验证
- 使用后台任务（background tasks）进行非阻塞操作
- 使用适当的状态码进行响应（201 表示创建，404 表示未找到等）
- 使用 APIRouter 按功能或资源组织路由
- 适当使用路径参数、查询参数和请求体
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 · 21 lines · 0 tokens per session scan A 200126051d14
fastapi is a cursor rule published in the GitHub repository WangTingYeYe/llm-agent-study (4 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 183 tokens. 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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