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tools llm ai AI Skills

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Categories: tools llm ai

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GitHub

arcanea-prompt-craft

frankxai

Master the Arcanean Prompt Language - advanced prompt engineering using mythological frameworks, constraint architecture, and the Centaur Principle for human-AI co-creation

GitHub

teacher-team

frankxai

Educational AI system with personalized learning, curriculum design, and adaptive mentorship

GitHub

arcanea-visionary-council

frankxai

Strategic AI council for product vision, creative direction, and long-term planning. Multiple perspectives from Strategist, Innovator, Futurist, and Synthesizer archetypes. Premium skill for decision-making.

GitHub

arcanea-teacher-mentor

frankxai

Personalized AI mentorship for learning any creative or technical skill. Adaptive teaching that meets you where you are and guides you to mastery. Premium skill for deep learning journeys.

GitHub

arcanea-centaur-mode

frankxai

Advanced human-AI co-creation methodology - the Centaur Principle in practice. Master the art of combining human creativity with AI capability for results neither could achieve alone.

GitHub

recipe-scraping

mschulkind

Guidelines and standards for scraping recipes from external sources using automated tools.

GitHub

podcast-generator

cmwen

Converts blog posts into podcast audio using Kokoro TTS engine. Use this when asked to generate podcasts, create audio, or run TTS for blog posts.

GitHub

respond-to-pr-review

kristofferremback

Fetch, analyze, and respond to PR review comments. Use when asked to check PR comments, address review feedback, respond to reviewers, or fix issues raised in code reviews.

GitHub

orchestrate

hdresearch

Orchestrate multiple AI agents across Vers VMs for parallel task execution

GitHub

context-compression

standardbeagle

This skill should be used when the user asks about "token efficiency", "compress responses", "reduce token usage", "minimize context", "compact format", "token optimization", or discusses reducing token consump...

GitHub

tool-design

standardbeagle

This skill should be used when the user asks to "design MCP tool", "create tool schema", "tool best practices", "input validation", "output schema", "error handling for tools", or discusses designing individual...

GitHub

client-guidance

standardbeagle

This skill should be used when the user asks about "error messages", "did you mean", "similar tools", "parameter suggestions", "schema hints", "MCP error handling", "guide the client", "helpful errors", "fuzzy...

GitHub

response-optimization

standardbeagle

This skill should be used when the user asks about "JSON flags", "token IDs", "cross-tool references", "progressive detail", "response optimization", "human and LLM readable", "automation flags", "confidence-ba...

GitHub

compliance-review

JesseNaranjo

This skill should be used when the user asks to "check CLAUDE.md compliance", "review against coding standards", "check AI agent instructions", "verify guidelines", "check coding conventions", "check naming con...

GitHub

tutorial-master

ernesto27

Expert tutorial and teaching skill for creating comprehensive, step-by-step explanations. Use when the user asks to explain something, create a tutorial, teach a concept, write documentation, create a guide, or...

GitHub

conversation-reader

MariusWilsch

Extract and read Claude conversation JSONL files with composable filters (discovery: rubber-duck). Evaluate at rubber-duck or at any point in the sesssion when task requires reading conversation history, verify...

GitHub

agent-dx-cli

rbergman

This skill provides patterns for designing command-line tools that agents can use effectively. Use when designing new CLIs, reviewing existing CLIs for agent compatibility, or adding agent-friendly features. Co...

GitHub

srt

rbergman

Sandbox Runtime (srt) patterns for CLI/autonomous Claude runs. For interactive sandboxing, use Claude Code's built-in `/sandbox` command instead.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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