发现 编程开发 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
ARCHITECT PHASE: Architectural design patterns, component templates, and system design guidance. Provides proven architectural patterns including microservices, layered architecture, event-driven systems, C4 d...
CODE PHASE (Database): Data layer implementation patterns and best practices. Provides schema design patterns, query optimization strategies, indexing guidelines, data integrity constraints, migration patterns...
CROSS-CUTTING: API contract design patterns for architects and implementers. Provides REST API design patterns, GraphQL schema design, API versioning strategies, error response formats, pagination patterns, an...
CODE PHASE (Backend): Server-side implementation patterns and best practices. Provides service layer patterns, API implementation guidance, error handling strategies, data validation approaches, middleware pat...
CROSS-CUTTING: Security patterns and best practices for ALL PACT phases. Provides OWASP Top 10 guidance, authentication/authorization patterns, input validation, secure coding practices, secrets management, an...
PREPARE PHASE: Research methodologies and documentation gathering workflows. Provides systematic research approaches, source evaluation criteria, documentation templates, API exploration techniques, and techno...
Record project activity, decisions, and outputs; query history and status. Provides institutional memory across sessions.
Create, organize, and prioritize tasks from briefs or brain dumps. Sync with Taskmaster MCP. Use to plan work, track status, and pick next steps.
Orchestrate project work: detect intent, run ADD checkpoints, and coordinate project-brief, task-engine, delegation-advisor, and project-logger.
Recommend who should do a task (Claude Code, Gemini, ChatGPT, Human, Taskmaster, MCPs) and generate handoff prompts.
Turn ideas/brain dumps into a structured project brief (problem, goals, scope, milestones, success criteria). Use when starting a project.
Integrate OpenAI Agent SDK with Google Gemini backend into FastAPI service using the official Google Gemini API via OpenAI compatibility layer.
Integrates Better Auth client with ChatKit UI or custom Next/Vite UI. Adds login/logout buttons, protected routes, session hooks.
Add selection-based Q&A functionality to ChatKit UI allowing users to ask about highlighted text with proper integration.
Generate the full production Dockerfile for the backend with multi-stage build, proper dependencies, and Hugging Face Spaces compatibility.
Generates Drizzle ORM schema files for users, sessions, tokens, OAuth accounts, and audit logs. Syncs schema to Neon Postgres.
Generate the complete RAG ingestion script to crawl textbook from sitemap.xml, chunk content, embed using Gemini, and push to Qdrant following MCP documentation.
Generate Hugging Face Spaces configuration files including runtime setup, environment variables, and deployment instructions.
Generate and maintain the FastAPI backend structure for the RAG chatbot with proper project organization.
Modify OpenAI ChatKit starter to use FastAPI backend instead of OpenAI API, including citation support and error handling.
Generate JSON schemas and Python handlers for Qdrant-based retrieval tools used by the RAG agent to search sitemap-crawled textbook content with URL citations.
Creates Better Auth configuration for frontend and backend: handlers, providers, middleware, session/token options. Uses Context7 MCP to retrieve Better Auth docs.
Implement the /chat endpoint that performs agent-based RAG reasoning with proper input validation and response formatting.
Provide local debugging scripts for Docker including build, run, and environment setup for development workflow.
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。