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Found 2,399 Skills
This skill should be used when the user wants to interact with their paper database — listing papers, searching content, showing paper details, adding papers, or exporting context. Matches queries like "search papers for X", "add this arXiv paper", "show equations from paper Y", "what papers do I have". Prefer CLI over MCP RAG tools for direct lookups.
Pull Bigdata.com (RavenPack) financial and news data through the official `bigdata-client` SDK and its public `/v1/*` REST endpoints when the Bigdata MCP server returns only pre-synthesized tearsheets but you need the machine-readable substrate underneath. MCP search returns prose chunks (text + relevance only — no per-chunk sentiment, no entity spans); its tearsheets give only aggregate values, not computable time series or per-field JSON. This skill bundles a verified, cost-guarded toolkit over the official REST API: annotated chunk search, entity/ISIN resolution, analyst estimates, calendar/surprise/ ratings/targets, financial statements, TTM metrics & ratios, prices, dividends, revenue segments, a daily entity-sentiment series, co-mention graph, screener, and batch search. Use it whenever the user mentions Bigdata.com, RavenPack, a `bd_v2_` key, the bigdata MCP, rp_entity_id, chunk/query_unit cost, or wants structured financials, fundamentals, prices, sentiment, or annotated news.
Microsoft Work IQ MCP integration for querying M365 data (emails, meetings, Teams, documents) with natural language. Enables searching your Microsoft 365 workspace directly from Claude Code.
This skill provides reusable implementation patterns extracted from the better-chatbot project for custom AI chatbot deployments. Use this skill when building AI chatbots with server action validators, tool abstraction systems, workflow execution, or multi-AI provider integration in your own projects (not contributing to better-chatbot itself). Use when: building AI chatbot features, implementing server action validators, creating tool abstraction layers, setting up multi-AI provider support, building workflow execution systems, adapting better-chatbot patterns to custom projects Keywords: AI chatbot patterns, server action validators, tool abstraction, multi-AI providers, workflow execution, MCP integration, validated actions, tool type checking, Vercel AI SDK patterns, chatbot architecture
Enables Claude to create, manage, and track projects and tasks in Asana via Playwright MCP
Use this skill when building AI voice agents with the ElevenLabs Agents Platform. This skill covers the complete platform including agent configuration (system prompts, turn-taking, workflows), voice & language features (multi-voice, pronunciation, speed control), knowledge base (RAG), tools (client/server/MCP/system), SDKs (React, JavaScript, React Native, Swift, Widget), Scribe (real-time STT), WebRTC/WebSocket connections, testing & evaluation, analytics, privacy/compliance (GDPR/HIPAA/SOC 2), cost optimization, CLI workflows ("agents as code"), and DevOps integration. Prevents 17+ common errors including package deprecation, Android audio cutoff, CSP violations, missing dynamic variables, case-sensitive tool names, webhook authentication failures, and WebRTC configuration issues. Provides production-tested templates for React, Next.js, React Native, Swift, and Cloudflare Workers. Token savings: ~73% (22k → 6k tokens). Production tested. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill to implement designs from Figma nodes or natural language to Vue 3 component or Nuxt pages using Mekari Pixel 3 design system. Requires a working Pixel MCP server connection.
Comprehensive academic textbook chapter writing system for medical/scientific content. Use when the user wants to: (1) Write a full textbook chapter (5,000-15,000 words) on any medical/scientific topic, (2) Generate a detailed table of contents with section word counts, (3) Research topics via PubMed MCP and compile 20-30 references, (4) Write section-by-section with proper citations in Vancouver format, (5) Create publishable academic content with Eric Topol-inspired voice and authentic human prose, (6) Get approval at TOC stage before writing begins, (7) Export well-structured chapters for textbook publication.
Find orphan functions, dangling imports, and dead code via GitNexus CLI (npx gitnexus@latest). CLI ONLY - NO MCP server exists, never use readMcpResource with gitnexus:// URIs. TRIGGERS - dead code, orphan functions, unused imports, dangling references, unreachable code.
Use when design, prototyping or referencing Figma files. Provides capabilities for inspecting design elements, extracting assets, generating code from designs, and managing Code Connect mappings via the figma-desktop MCP server.
Generate type-safe React Query hooks, Prisma-like ORM client, or inquirerer-based CLI from GraphQL endpoints, schema files/directories, databases, or PGPM modules using @constructive-io/graphql-codegen. Also generates documentation (README, AGENTS.md, skills/, mcp.json). Use when asked to "generate GraphQL hooks", "generate ORM", "generate CLI", "set up codegen", "generate docs", "generate skills", "export schema", or when implementing data fetching for a PostGraphile backend.
Add custom local tools to ToolUniverse and use them alongside the 1000+ built-in tools. Use this skill when a user wants to: create their own tool for a private or custom API, add a local tool to their workspace, integrate an internal service with ToolUniverse, or use a custom tool via the MCP server or Python API. Covers both the JSON config approach (easiest, no Python needed) and the Python class approach (full control). Also covers how to verify tools loaded correctly and how to call them. Also covers the plugin package approach for reusable, shareable, pip-installable tool sets.