Total 50,604 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Set up and optimize repositories for AI coding agents. Creates minimal AGENTS.md, CLAUDE.md symlink, docs/REQUIREMENTS.md, docs/BUSINESS-RULES.md, feedback loops, and deterministic enforcement (Claude Code hooks, OpenCode plugins). Use when user wants to make a repo AI-friendly, set up AGENTS.md/CLAUDE.md, document requirements/business rules for AI, add pre-commit hooks for AI workflows, or optimize codebase structure for coding agents.
Assistant for newapi (new-api), an open-source unified AI gateway platform (https://github.com/QuantumNous/new-api). Use when the user asks about New API, managing models, groups, balance, or tokens, or securely copying keys, applying them to config files, or using them in commands without exposing secrets.
在远程服务器上一键部署 OpenClaw。当用户需要安装 OpenClaw、部署 OpenClaw、配置 OpenClaw 到服务器时使用
This skill should be used when the user asks to "build an MCP server", "create an MCP tool", "expose resources with MCP", "write an MCP client", or needs guidance on the Model Context Protocol Python SDK best practices, transports, server primitives, or LLM context integration.
Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after idea-tournament), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing idea tournaments or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use idea-tournament).
Agent-IM Conversation Skill - Create sessions, send messages such as image/video generation requests via OpenAPI, and query session progress. This skill is activated when users need to generate images/videos or query current session messages.
Generate a production-ready AbsolutelySkilled skill from any source: GitHub repos, documentation URLs, or domain topics (marketing, sales, TypeScript, etc.). Triggers on /skill-forge, "create a skill for X", "generate a skill from these docs", "make a skill for this repo", "build a skill about marketing", or "add X to the registry". For URLs: performs deep doc research (README, llms.txt, API references). For domains: runs a brainstorming discovery session with the user to define scope and content. Outputs a complete skill/ folder with SKILL.md, evals.json, and optionally sources.yaml, ready to PR into the AbsolutelySkilled registry.
Analyze a project's past Codex sessions, memory files, and existing local skills to recommend the highest-value skills to create or update. Use when a user asks what skills a project needs, wants skill ideas grounded in real project history, wants an audit of current project-local skills, or wants recommendations for updating stale or incomplete skills instead of creating duplicates.
Orchestrate multi-agent coding tasks via Claude DevFleet — plan projects, dispatch parallel agents in isolated worktrees, monitor progress, and read structured reports.
Personal intelligence agent that aggregates 27 OSINT data sources into a self-hosted Jarvis-style dashboard with Telegram/Discord bots, LLM analysis, and real-time alerts.
Install and use the Edict (三省六部) multi-agent orchestration system with 12 specialized AI agents, real-time kanban dashboard, and audit trails
A meta-skill that understands task requirements, dynamically selects appropriate skills, tracks successful skill combinations using agent-memory-mcp, and prevents skill overuse for simple tasks.