Loading...
Loading...
Found 479 Skills
Generates Bill of Materials (BOM) from project descriptions for Arduino/ESP32/RP2040 projects. Use when user needs component lists, parts shopping lists, cost estimates, or asks "what parts do I need". Outputs formatted BOMs with part numbers, quantities, suppliers (DigiKey, Mouser, Amazon, AliExpress), and compatibility warnings. Run scripts/generate_bom.py for xlsx/csv export.
Identifies anti-patterns specific to amplihack philosophy. Use when reviewing code for quality issues or refactoring. Detects: over-abstraction, complex inheritance, large functions (>50 lines), tight coupling, missing __all__ exports. Provides specific fixes and explanations for each smell.
Generate audio tones, noise, DTMF signals, and simple sound effects programmatically. Export to WAV or MP3 format.
Record high-quality podcasts and interviews with Riverside - manage recordings, transcripts, and exports
Analyze UI design screenshots and generate React components with TypeScript and Tailwind CSS. Use this skill when the user provides UI mockups, design screenshots, or Figma exports and requests implementation. Provides detailed layout analysis, component breakdown, design token extraction, and production-ready code generation following best practices.
Intelligent software copyright application material generation tool. Automatically analyzes project source code, generates software manuals and source code documents that meet the requirements of software copyright applications. Supports keyword search, intelligent source code analysis, formatted output, and PDF export.
Retrieve detailed revenue breakdown by geographic segment for public companies. Use when analyzing regional exposure, geographic concentration, international expansion, or currency risk assessment.
Unified issue resolution pipeline with source selection. Plan issues via AI exploration, convert from artifacts, import from brainstorm sessions, form execution queues, or export solutions to task JSON. Triggers on "issue:plan", "issue:queue", "issue:convert-to-plan", "issue:from-brainstorm", "export-to-tasks", "resolve issue", "plan issue", "queue issues", "convert plan to issue".
Retrieve paper metadata from arXiv using keyword queries and save results as JSONL (`papers/papers_raw.jsonl`). **Trigger**: arXiv, arxiv, paper search, metadata retrieval, 文献检索, 论文检索, 拉取元数据, 离线导入. **Use when**: 需要一个初始论文集合（survey/snapshot 的 Stage C1），来源为 arXiv（在线检索或离线导入 export）。 **Skip if**: 已经有可用的 `papers/papers_raw.jsonl`，或数据源不是 arXiv。 **Network**: 在线检索需要网络；离线 `--input <export.*>` 不需要网络。 **Guardrail**: 只做 metadata；不要在 `output/` 写长 prose。
High-performance Rust web crawler with stealth mode, LLM-ready Markdown export, multi-format output, sitemap discovery, and robots.txt support. Optimized for content extraction, site mapping, structure analysis, and LLM/RAG pipelines.
Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespans, middleware system (8 built-in types), server composition (import/mount), OAuth Proxy, authentication patterns, icons, OpenAPI integration, client configuration, cloud deployment (FastMCP Cloud), error handling, and production patterns. It prevents 25+ common errors including storage misconfiguration, lifespan issues, middleware order errors, circular imports, module-level server issues, async/await confusion, OAuth security vulnerabilities, and cloud deployment failures. Includes templates for basic servers, storage backends, middleware, server composition, OAuth proxy, API integrations, testing, and self-contained production architectures. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp
Production-tested setup for Zustand state management in React applications with TypeScript. This skill provides comprehensive patterns for building scalable, type-safe global state. Use when: setting up global state in React, migrating from Redux or Context API, implementing state persistence with localStorage, configuring TypeScript with Zustand, using slices pattern for modular stores, adding devtools middleware for debugging, handling Next.js SSR hydration, or encountering hydration errors, TypeScript inference issues, or persist middleware problems. Prevents 5 documented issues: Next.js hydration mismatches, TypeScript double parentheses syntax errors, persist middleware export errors, infinite render loops, and slices pattern type inference failures. Keywords: zustand, state management, React state, TypeScript state, persist middleware, devtools, slices pattern, global state, React hooks, create store, useBoundStore, StateCreator, hydration error, text content mismatch, infinite render, localStorage, sessionStorage, immer middleware, shallow equality, selector pattern, zustand v5