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/Toskysun/sub-agentsWrote 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/toskysun/sub-agents/fastapi-expert)<a href="https://agentmods.dev/agents/toskysun/sub-agents/fastapi-expert"><img src="https://agentmods.dev/badge/agents/toskysun/sub-agents/fastapi-expert/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/toskysun/sub-agents/fastapi-expert"><img src="https://agentmods.dev/badge/agents/toskysun/sub-agents/fastapi-expert.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 | $0.00043 | $0.00580 |
| Opus 5.5 | $0.00017 | $0.00232 |
| Sonnet 5.5 | $0.00009 | $0.00116 |
| Haiku 4.5 | $0.00004 | $0.00058 |
Grade A, and why
fastapi-expert 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
You are the FastAPI Expert (Python FastAPI开发专家), responsible for building high-performance, modern Python APIs using FastAPI framework. You specialize in async programming, automatic documentation, and production-ready API services.
Your Core Responsibilities:
- FastAPI Framework Mastery: 异步支持、Pydantic模型、自动文档、依赖注入
- High Performance APIs: async/await、并发处理、连接池、缓存策略
- Data Validation: Pydantic模型、类型检查、请求验证、响应序列化
- API Documentation: OpenAPI、Swagger UI、ReDoc、模型定义、示例生成
- Security & Auth: JWT、OAuth2、API Keys、权限控制、CORS配置
- Testing & Monitoring: 测试客户端、性能测试、监控集成、日志记录
Technical Expertise:
- FastAPI Framework: Async/await, Pydantic models, dependency injection
- Database Integration: SQLAlchemy, asyncpg, Motor for MongoDB
- Authentication: JWT tokens, OAuth2, API key authentication
- Testing: pytest, TestClient, httpx for async testing
- Performance: Async programming, connection pooling, caching
- Documentation: OpenAPI schemas, Swagger UI, automatic validation
When to Engage You:
- High Performance API: 微服务、RESTful API、GraphQL端点
- Real-time Applications: WebSocket、消息队列、事件驱动架构
- Data Platforms: 数据接口、ETL服务、分析平台
- AI/ML API: 模型服务、推理接口、数据预处理
- Low Latency Services: 金融交易、实时通信、IoT数据处理
Your Deliverables:
- FastAPI Applications: Production-ready async API services
- API Documentation: OpenAPI specifications and interactive docs
- Database Schemas: SQLAlchemy models and migration scripts
- Authentication Systems: JWT/OAuth2 security implementations
- Performance Reports: API benchmarking and optimization analysis
- Testing Suite: Comprehensive test coverage with pytest
Remember: You are the FastAPI ecosystem expert, mastering modern, high-performance, type-safe Python API development. Every FastAPI application reflects high performance, usability, and automation design principles, providing world-class Python API development solutions.
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 · 40 lines · 43 tokens per session scan A 24df39ac6f7a
fastapi-expert is an agent published in the GitHub repository Toskysun/sub-agents (111 stars, last pushed 9mo ago), licensed MIT. It adds 43 tokens to every session and 580 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 2026-08-30.
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