Total 56,990 skills, AI & Machine Learning has 9477 skills
Showing 12 of 9477 skills
Autonomous development agent that picks tasks from a project board (Jira, ClickUp, GitHub Issues), explores the codebase, implements the solution, opens a PR, and notifies the team. Configurable per-project via project files in ~/.config/delivering-tickets/projects/. Use this skill when the user asks to "work on a ticket", "pick up a task", "implement issue X", "work autonomously on the board", "take the next task", or any variation of autonomous task execution from a project board. Also triggers when the user mentions delivering-tickets, project configuration, or wants to set up autonomous development workflows for their team. Available commands: /delivering-tickets (start), /delivering-tickets:check (check replies), /delivering-tickets:status (workflow status), /delivering-tickets:setup (verify environment), /delivering-tickets:project (manage projects). Do NOT use for general coding without a ticket, standalone code reviews, project setup without a board configured, or questions unrelated to task execution from a project board.
OpenClaw learning expert that retrieves and synthesizes information from official documentation (https://docs.openclaw.ai) and GitHub repository (https://github.com/openclaw/openclaw). Use this skill whenever the user asks questions about OpenClaw, including installation, configuration, API usage, concepts, troubleshooting, best practices, or any OpenClaw-related inquiries. Triggers include OpenClaw questions about features, implementation, usage, setup, or any openclaw-related topics.
Apply DriveMind, the calm reliability layer for AI agents. Use when a task needs steady follow-through, clearer progress, stronger persistence without recklessness, explicit safety boundaries, human-in-the-loop collaboration, post-task review, reusable memory, or when the user says things like 'keep pushing', 'don’t stop too early', 'be steady', 'if risk is unclear ask me', 'review this after', or 'write down the lesson'.
Orchestrate a specialized software development agent team. Receive user requests, classify task type, select the matching workflow, delegate each step to specialist agents via the Agent tool, and assemble the final output. Use when the user needs multi-step software development involving architecture, implementation, testing, security review, or code review. Also use for production incident investigation — when the user reports a live system issue, service outage, pod crash, data anomaly, or needs root cause analysis using kubectl, psql, argocd, or docker. Trigger this skill whenever a task involves more than one concern (e.g., "add a new endpoint" needs BA + Architect + Developer + QA + Security), when the user mentions team coordination, agent delegation, or when the work clearly benefits from multiple specialist perspectives rather than a single implementation pass.
Coin comparison. Use this skill whenever the user asks to compare two or more coins. Trigger phrases include: compare, versus, vs, which is better, difference. MCP tools: info_marketsnapshot_get_market_snapshot, info_coin_get_coin_info per coin (or batch/search when available).
Market overview. Use this skill whenever the user asks about overall market. Trigger phrases include: how is the market, market overview, what is happening in crypto. MCP tools: info_marketsnapshot_get_market_overview, info_coin_get_coin_rankings, info_platformmetrics_get_defi_overview, news_events_get_latest_events, info_macro_get_macro_summary.
AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.
Fix incorrect SKILL.md files when a skill has wrong instructions or outdated API references
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
Analyze a codebase and recommend Claude Code automations (hooks, subagents, skills, plugins, MCP servers). Use when user asks for automation recommendations, wants to optimize their Claude Code setup, mentions improving Claude Code workflows, asks how to first set up Claude Code for a project, or wants to know what Claude Code features they should use.
Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production. This skill covers LLM integration patterns, RAG architecture, prompt engineering that scales, AI UX that users trust, and cost optimization that doesn't bankrupt you. Use when: keywords, file_patterns, code_patterns.
Run LLMs and AI models on Cloudflare's GPU network with Workers AI. Includes Llama 4, Gemma 3, Mistral 3.1, Flux images, BGE embeddings, streaming, and AI Gateway. Handles 2025 breaking changes. Prevents 7 documented errors. Use when: implementing LLM inference, images, RAG, or troubleshooting AI_ERROR, rate limits, max_tokens, BGE pooling, context window, neuron billing, Miniflare AI binding, NSFW filter, num_steps.