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All Skills

Total 57,828 skills, AI & Machine Learning has 9617 skills

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Showing 12 of 9617 skills

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AI & Machine Learningravi-hq/deepthink-skills

helmer

Hamilton Helmer's 7 Powers framework applied to a business. Spawns a team of specialist agents — Power Cartographer, Lifecycle Timer, Counter-Positioning Scout, and Moat Devil's Advocate — who each apply a distinct lens from Helmer's taxonomy. The lead synthesizes into a Power Inventory (what you have), Power Pipeline (what's achievable given your stage), and the honest Helmer Verdict. Use when the user says "helmer this", "apply 7 powers", "what power does this company have", "is this a moat", "diagnose my competitive position", or proposes a business and wants strategic analysis. Works standalone or after /thiel (which confirms you need a monopoly) or /munger (which asks if the economics are durable).

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25
AI & Machine Learningmindfold-ai/marketplace

trellis-meta

Meta-skill for understanding and customizing Mindfold Trellis — the all-in-one AI workflow system for 11 AI coding platforms (Claude Code, Cursor, OpenCode, iFlow, Codex, Kilo, Kiro, Gemini CLI, Antigravity, Qoder, CodeBuddy). Documents the original Trellis system design including architecture, commands, hooks, multi-agent pipelines, monorepo support, and task lifecycle hooks. Use when understanding Trellis architecture, customizing workflows, adding commands or agents, troubleshooting issues, or adapting Trellis to specific projects. Modifications should be recorded in a project-local trellis-local skill, not here.

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25
AI & Machine Learningruvnet/ruflo

agent-swarm-memory-manager

Agent skill for swarm-memory-manager - invoke with $agent-swarm-memory-manager

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25
AI & Machine Learningruvnet/ruflo

agent-swarm-pr

Agent skill for swarm-pr - invoke with $agent-swarm-pr

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25
AI & Machine Learningruvnet/ruflo

agent-v3-integration-architect

Agent skill for v3-integration-architect - invoke with $agent-v3-integration-architect

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25
AI & Machine Learningruvnet/ruflo

agent-performance-monitor

Agent skill for performance-monitor - invoke with $agent-performance-monitor

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25
AI & Machine Learninglaguagu/claude-code-nextj...

nextjs-chatbot

Production-grade Next.js chatbot builder. Covers tool calling with human-in-the-loop (HITL) approval, PostgreSQL session persistence, GDPR consent gating, SQL-first search, per-tool UI rendering, message feedback, and follow-up suggestions. Use when building chat apps, conversational AI interfaces, customer support bots, or any chatbot needing database-backed sessions, tool approval workflows, consent gating, or custom tool output components. Reference implementation: fair-helpdesk project.

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25
AI & Machine Learninghuggingface/skills

huggingface-trackio

Track and visualize ML training experiments with Trackio. Use when logging metrics during training (Python API), firing alerts for training diagnostics, or retrieving/analyzing logged metrics (CLI). Supports real-time dashboard visualization, alerts with webhooks, HF Space syncing, and JSON output for automation.

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25
AI & Machine Learninghuggingface/skills

huggingface-llm-trainer

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

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25
7 scripts/Checked
AI & Machine Learninggithub/awesome-copilot

onboard-context-matic

Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).

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25
AI & Machine Learninggentleman-programming/sdd...

sdd-explore

Explore and investigate ideas before committing to a change. Trigger: When the orchestrator launches you to think through a feature, investigate the codebase, or clarify requirements.

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25
AI & Machine Learningwyattowalsh/agents

research

General-purpose deep research with multi-source synthesis and confidence-scored findings. Auto-classifies complexity from quick lookup to exhaustive investigation. Cross-validates across independent sources with anti-hallucination verification, contradiction detection, and bias auditing. Produces synthesis products with evidence chains and provenance. Resumable journal sessions. Use when investigating technical topics, academic questions, market analysis, competitive intelligence, architecture decisions, technology evaluation, fact-checking, literature review, or trend analysis. NOT for code review (use honest-review), strategic decisions (use wargame), multi-perspective debate (use host-panel), or simple factual Q&A answerable in one search.

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25
4 scripts/Attention
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