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All Skills

Total 54,152 skills, AI & Machine Learning has 8999 skills

Categories

Showing 12 of 8999 skills

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AI & Machine Learningseckatie/katies-ai-skills

llm

Access and interact with Large Language Models from the command line using Simon Willison's llm CLI tool. Supports OpenAI, Anthropic, Gemini, Llama, and dozens of other models via plugins. Features include chat sessions, embeddings, structured data extraction with schemas, prompt templates, conversation logging, and tool use. This skill is triggered when the user says things like "run a prompt with llm", "use the llm command", "call an LLM from the command line", "set up llm API keys", "install llm plugins", "create embeddings", or "extract structured data from text".

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34
2 scripts/Checked
AI & Machine Learningdokhacgiakhoa/antigravity...

github-mcp

Official GitHub Model Context Protocol Server for repository management.

🇺🇸|EnglishTranslated
34
AI & Machine Learningcluesmith/codev

consult

AI consultation CLI quick reference. Use when running consult commands to check syntax for general queries, protocol reviews, and stats across Gemini, Codex, and Claude.

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34
AI & Machine Learningjimlee2048/skills

comfyui-nodes-dev

Develop ComfyUI server-side V3 custom nodes (Python) using Comfy API v0_0_2/latest, schema-based inputs/outputs, ComfyExtension entrypoints, and UI preview helpers. Use when asked to create or update ComfyUI custom_nodes, V3 nodes, or Comfy API-based nodepacks.

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34
1 scripts/Checked
AI & Machine Learningbankrbot/openclaw-skills

bankr

AI-powered crypto trading agent via natural language. Use when the user wants to trade crypto (buy/sell/swap tokens), check portfolio balances, view token prices, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading strategies, submit raw transactions, execute calldata, or send transaction JSON. Supports Base, Ethereum, Polygon, Solana, and Unichain. Comprehensive capabilities include trading, portfolio management, market research, NFT operations, prediction markets, leverage trading, DeFi operations, automation, and arbitrary transaction submission.

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34
4 scripts/Attention
AI & Machine Learningigorwarzocha/opencode-wor...

skill-creator

Guide for creating effective opencode skills. Use for creating or updating skills that extend agent capabilities with specialized knowledge, workflows, or tool integrations. Examples: - user: "Create a skill for git workflows" → define SKILL.md with instructions and examples - user: "Add examples to my skill" → follow the user: "query" → action pattern - user: "Update skill description" → use literal block scalar and trigger contexts - user: "Structure a complex skill" → organize with scripts/ and references/ directories - user: "Validate my skill" → check structure, frontmatter, and discovery triggers

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34
3 scripts/Checked
AI & Machine Learningopendndapps/ogt-skills

ogt-cli-claude

Run Claude Code CLI for complex tasks, code generation, analysis, and research. Uses Anthropic OAuth (included in Claude Pro). Use for extended thinking, code review, architecture decisions. Preferred for load balancing sub-agent work (35% weight).

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34
1 scripts/Attention
AI & Machine Learningwyattowalsh/agents

host-panel

Host simulated panel discussions and debates among AI-simulated domain experts. Supports roundtable, Oxford-style, and Socratic formats with heterogeneous expert personas, anti-groupthink mechanisms, and structured synthesis. Use when exploring complex topics from multiple expert perspectives, testing argument strength, academic brainstorming, or understanding trade-offs in decisions. NOT for one-on-one conversations, simple Q&A, or real-time debates.

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34
AI & Machine Learninggithub/awesome-copilot

mcp-create-adaptive-cards

Skill converted from mcp-create-adaptive-cards.prompt.md

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34
AI & Machine Learninggithub/awesome-copilot

mcp-deploy-manage-agents

Skill converted from mcp-deploy-manage-agents.prompt.md

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34
AI & Machine Learningwshobson/agents

rag-implementation

Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

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34
AI & Machine Learningwshobson/agents

llm-evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

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34
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