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Found 2,200 Skills
A comprehensive tool for searching, analyzing, and extracting Bilibili video content. This skill must be triggered whenever users mention Bilibili, provide Bilibili links (bilibili.com, b23.tv), request to search for specific videos, extract video metadata (title, uploader, view count, description), obtain video subtitles, or retrieve comments/barrage for analysis and summarization. It supports handling 412 risk control prompts and Cookie injection.
Use this skill when working with Mastra - the TypeScript AI framework for building agents, workflows, tools, and AI-powered applications. Triggers on creating agents, defining workflows, configuring memory, RAG pipelines, MCP client/server setup, voice integration, evals/scorers, deployment, and Mastra CLI commands. Also triggers on "mastra dev", "mastra build", "mastra init", Mastra Studio, or any Mastra package imports.
Triggers on cluttered folders, file chaos, storage cleanup, or directory restructuring needs. TRIGGER WHEN: organizing messy folders (Downloads, Desktop, Documents), finding duplicate files, cleaning up old files, restructuring project directories, separating work from personal files, or automating file cleanup tasks DO NOT TRIGGER WHEN: the task is outside the specific scope of this component.
Manages permanent memory storage for decisions, blockers, context, preferences, and procedures. Use when user says "remember", "save this decision", "what did we decide", "recall", "search memories", "any blockers", or when making important architectural decisions. Provides SDAM compensation through external memory.
NotebookLM integration patterns for external RAG, research synthesis, studio content generation (audio, cinematic video, slides, infographics, mind maps), and knowledge management. Use when creating notebooks, adding sources, generating audio/video, or querying NotebookLM via MCP.
Integrate react-native-reanimated-dnd for drag-and-drop, sortable lists, sortable grids, and drop zones in React Native apps. Covers components, hooks, and all configuration options.
Guide for selecting and executing the correct pytest suites (unit, integration, redis, R2, routing rules, magic link) with environment setup and coverage expectations.
Coaches end-to-end ML system design interviews covering inference pipelines, recommendation systems, RAG, feature stores, and monitoring. Use for L6+ design rounds, ML architecture whiteboarding, system design practice, serving tradeoff analysis. Activate on "ML system design", "ML interview", "recommendation system design", "RAG architecture", "feature store design", "model serving". NOT for coding interviews, behavioral questions, ML theory quizzes, or paper implementations.
Generates comprehensive, workable unit tests for any programming language using a multi-agent pipeline. Use when asked to generate tests, write unit tests, improve test coverage, add test coverage, create test files, or test a codebase. Supports C#, TypeScript, JavaScript, Python, Go, Rust, Java, and more. Orchestrates research, planning, and implementation phases to produce tests that compile, pass, and follow project conventions.
Guide the design and maintenance of recordkeeping programs under SEC Rules 17a-3, 17a-4, and 204-2. Use when the user asks about document retention schedules, how long to keep trade records or customer complaints, WORM storage requirements, email or text message archiving, social media capture, BYOD compliance policies, or electronic storage audit trails. Also trigger when users mention 'we got an exam request for records', 'migrating to a new archiving vendor', 'blotter retention', 'order ticket requirements', 'off-channel communications', 'WhatsApp archiving', or ask how long specific records must be kept.
Use when choosing a testing approach for a project — selecting frameworks, defining coverage thresholds, setting up test infrastructure, and establishing testing patterns. Triggers: new project setup, CI/CD pipeline design, coverage audit, test framework migration, quality standard definition.
Expert knowledge for Microsoft Foundry (aka Azure AI Foundry) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Foundry agents with Azure OpenAI, vector search/RAG, Sora video, realtime audio, or MCP/LangChain APIs, and other Microsoft Foundry related development tasks. Not for Microsoft Foundry Classic (use microsoft-foundry-classic), Microsoft Foundry Local (use microsoft-foundry-local), Microsoft Foundry Tools (use microsoft-foundry-tools).