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Found 1,346 Skills
Give your AI agents capabilities through tools (function calling). Helps you identify what your AI needs to do, create tool definitions, and attach them to AI Config variations.
Use this skill whenever the user wants to interact with an n8n instance via its public REST API. Triggers include: listing, creating, updating, deleting, activating or deactivating workflows; viewing or managing executions; managing credentials, tags, variables, users, or projects; auditing instance activity; triggering workflow runs; checking execution status; or any automation task involving the n8n API. Also use for requests like "show my n8n workflows", "run workflow X", "list failed executions", "create a tag in n8n", "manage n8n variables", or "check n8n audit log". Always use this skill for any n8n API interaction — it defines the correct endpoints, authentication, and patterns.
Generate images with gpt-image-2 through an OpenAI-compatible Image API using the current OPENAI_API_KEY, OPENAI_BASE_URL, or CUSTOM_IMAGE_URL environment variables. Use when the user asks to call gpt-image-2 via API/CLI, /v1/images/generations, the prior /api/image/generate endpoint flow, or wants the faster API route instead of Codex CLI image_generation/session extraction.
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.
A-share Market Daily Review System. Actively invoked when users mention needs such as market review, market analysis, or tomorrow's market prediction. Covers: Market Environment, Sentiment Cycle, Main Line Identification, Capital Monitoring, Post-Market Variables, Tomorrow's Combat Map. For research reference only, does not constitute securities investment consulting business or investment advice.
How to launch distributed Megatron-LM training jobs on a SLURM cluster. Covers a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules across hardware and parallelism modes, container conventions, monitoring, and per-rank failure diagnosis.
Use when asking about Rust code style or best practices. Keywords: naming, formatting, comment, clippy, rustfmt, lint, code style, best practice, P.NAM, G.FMT, code review, naming convention, variable naming, function naming, type naming, 命名规范, 代码风格, 格式化, 最佳实践, 代码审查, 怎么命名
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Use when asked to "build habit-forming products", "Hooked model", "trigger action reward investment", "create sticky behavior loops", or "design habit loops". Helps design products that form unprompted user habits. The Hooked Model (created by Nir Eyal) explains how products create habits through Trigger, Action, Variable Reward, and Investment.
Tailwind CSS utility patterns with shadcn/ui component usage, theming via CSS variables, and responsive design. Use when styling components, installing shadcn components, implementing dark mode, or creating consistent design systems.
Analyze drug safety signals from FDA adverse event reports, label warnings, and pharmacogenomic data. Calculates disproportionality measures (PRR, ROR), identifies serious adverse events, assesses pharmacogenomic risk variants. Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment.
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