Total 50,524 skills, AI & Machine Learning has 8481 skills
Showing 12 of 8481 skills
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Self-evolving AI agent system with 26 tools, three-layer memory, MCP plugins, and 24/7 self-repair in pure Python.
A team of 10 AI agents that manage your Obsidian vault for knowledge, nutrition, and mental wellness using Claude Code
Transform AI-generated content into authentic, human-sounding writing. Covers AI pattern detection, natural writing rhythm restoration, voice injection, brand personality application, and authenticity scoring. Use when content sounds robotic, uses AI cliches, lacks personality, reads like committee writing, or when user mentions AI content, make it human, add personality, sounds robotic, fix AI writing, content authenticity, AI detection, or humanize content.
Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.
Interact with the learning system: show stats, list/search accumulated knowledge, and graduate mature entries into agents/skills. Backed by learning.db (SQLite + FTS5). Use when user says "retro", "retro list", "retro search", "retro graduate", "check knowledge", "what have we learned", "knowledge health", "graduate knowledge".
Break a design document into wave-ordered implementation tasks with domain agent assignments. Use after /feature-design produces a design doc. Use for "plan feature", "break down design", "create tasks", or "/feature-plan". Do NOT use without a design doc or for simple single-task work.
Weighted decision scoring framework for architectural and technology choices. Frames decisions with 2-4 options, scores against weighted criteria, detects close calls, and records decisions in the active ADR or task plan. Use when: "should I use X or Y", "which approach", "compare options", "trade-offs between", "help me decide", "evaluate alternatives"
Verifies user credentials on Moca chain testnet via AIR agent sessions. Use when a user wants to verify a credential, list available verification programs, or check credential compliance.
Connect WeChat to AI agents (Claude, Codex, Gemini, Kimi, etc.) using the WeClaw bridge in Go.
Design exploration with parallel agents. Use when brainstorming ideas, exploring solutions, or comparing alternatives.
Use when building features that answer questions from private data, documents, policies, or time-sensitive information — RAG architecture, chunking strategies, hybrid search, re-ranking, vector databases, evaluation, agentic RAG, multimodal RAG...