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Found 1,897 Skills
Blender to web export workflows for 3D models and animations. Use this skill when exporting Blender models to glTF for web, optimizing 3D assets for Three.js or Babylon.js, batch processing models with Python scripts, automating Blender workflows, or creating web-ready 3D pipelines. Triggers on tasks involving Blender glTF export, bpy scripting, 3D asset optimization, model compression, texture baking, or Blender automation. Exports models for threejs-webgl, react-three-fiber, and babylonjs-engine skills.
Tiger Brokers OpenAPI Python SDK — complete skills for AI coding tools. Covers SDK setup, market data queries, stock/futures/options trading, real-time push subscriptions, CLI command-line tool, and MCP server integration. Use when building trading applications, querying market data, placing orders, using the tigeropen CLI, or integrating Tiger Brokers API with AI editors. 老虎证券 OpenAPI Python SDK 完整技能集。涵盖 SDK 配置、行情查询、股票/期货/期权交易、实时推送订阅、CLI 命令行工具、MCP Server 集成。适用于构建交易应用、查询行情数据、下单交易、使用 tigeropen CLI、或将老虎 API 集成到 AI 编辑器。
Lobstr.io platform help — no-code web scraping platform with 50+ ready-made scrapers for Google Maps, LinkedIn Sales Navigator, Twitter, YouTube, and more. Features cookie-based login sync, scheduled automation, multi-threading, and a full API with Python SDK and MCP Server. Use when configuring a Lobstr scraper, exporting data to Google Sheets or S3, setting up scheduled scraping, working with the Lobstr API or Python SDK, or managing credits. Do NOT use for general prospect list strategy (use /sales-prospect-list), cross-platform enrichment strategy (use /sales-enrich), or integration strategy (use /sales-integration).
Use when integrating crates or ecosystem questions. Keywords: E0425, E0433, E0603, crate, cargo, dependency, feature flag, workspace, which crate to use, using external C libraries, creating Python extensions, PyO3, wasm, WebAssembly, bindgen, cbindgen, napi-rs, cannot find, private, crate recommendation, best crate for, Cargo.toml, features, crate 推荐, 依赖管理, 特性标志, 工作空间, Python 绑定
Use when learning Rust concepts. Keywords: mental model, how to think about ownership, understanding borrow checker, visualizing memory layout, analogy, misconception, explaining ownership, why does Rust, help me understand, confused about, learning Rust, explain like I'm, ELI5, intuition for, coming from Java, coming from Python, 心智模型, 如何理解所有权, 学习 Rust, Rust 入门, 为什么 Rust
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.
Autonomous polyglot monorepo bootstrap meta-prompt. TRIGGERS - new monorepo, polyglot setup, scaffold Python+Rust+Bun, monorepo from scratch.
IDA Pro Python scripting for reverse engineering. Use when writing IDAPython scripts, analyzing binaries, working with IDA's API for disassembly, decompilation (Hex-Rays), type systems, cross-references, functions, segments, or any IDA database manipulation. Covers ida_* modules (50+), idautils iterators, and common patterns.
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
Dual skill for deploying scientific models. FastAPI provides a high-performance, asynchronous web framework for building APIs with automatic documentation. Streamlit enables rapid creation of interactive data applications and dashboards directly from Python scripts. Load when working with web APIs, model serving, REST endpoints, interactive dashboards, data visualization UIs, scientific app deployment, async web frameworks, Pydantic validation, uvicorn, or building production-ready scientific tools.
Diagnose and fix bugs using runtime execution traces. Use when debugging errors, analyzing failures, or finding root causes in Python, Node.js, or Java applications.
Creates and manages project artifacts (research, spikes, analysis, plans) using templated scripts. Use when asked to "create an ADR", "research topic", "spike investigation", "implementation plan", or "create analysis". Provides standardized structure, naming conventions, and helper scripts for artifact organization. Works with .claude/artifacts/ directory, Python scripts, and markdown templates.