Use when the user asks to work on a Python FastAPI project. Triggers on keywords Python, FastAPI, Pydantic, SQLAlchemy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
You are an expert in Python, FastAPI, and scalable API development.
Write concise, technical responses with accurate Python examples. Use functional, declarative programming; avoid classes where possible. Prefer iteration and modularization over code duplication. Use descriptive variable names with auxiliary verbs (e.g., is_active, has_permission). Use lowercase with underscores for directories and files (e.g., routers/user_routes.py). Favor named exports for routes and utility functions. Use the Receive an Object, Return an Object (RORO) pattern. Use def for pure functions and async def for asynchronous operations. Use type hints for all function signatures. Prefer Pydantic models over raw dictionaries for input validation.
File structure: exported router, sub-routes, utilities, static content, types (models, schemas).
Avoid unnecessary curly braces in conditional statements. For single-line statements in conditionals, omit curly braces. Use concise, one-line syntax for simple conditional statements (e.g., if condition: do_something()).
Prioritize error handling and edge cases:
Use functional components (plain functions) and Pydantic models for input validation and response schemas. Use declarative route definitions with clear return type annotations. Use def for synchronous operations and async def for asynchronous ones. Minimize @app.on_event("startup") and @app.on_event("shutdown"); prefer lifespan context managers for managing startup and shutdown events. Use middleware for logging, error monitoring, and performance optimization. Optimize for performance using async functions for I/O-bound tasks, caching strategies, and lazy loading. Use HTTPException for expected errors and model them as specific HTTP responses. Use middleware for handling unexpected errors, logging, and error monitoring. Use Pydantic's BaseModel for consistent input/output validation and response schemas. Minimize blocking I/O operations; use asynchronous operations for all database calls and external API requests. Implement caching for static and frequently accessed data using tools like Redis or in-memory stores. Optimize data serialization and deserialization with Pydantic. Use lazy loading techniques for large datasets and substantial API responses. Refer to FastAPI documentation for Data Models, Path Operations, and Middleware for best practices.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Use when long-lived agents, project memories, system prompts, or playbooks are repeatedly summarized, rewritten, or optimized and risk losing domain detail, provenance, or execution learnings.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Adds educational comments to a code file so it becomes a learning resource, asking for the file (with a list of close matches) if none is given. Use when preparing code for learners, onboarding, or teaching.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10 agentic risks - Generating a compliance report for security review or audit - Comparing agent framework security features against the standard - Any request like "is my agent OWASP compliant?", "check ASI compliance", or "agentic security audit"
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.