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SkillsMP は majiayu000/claude-skill-registry から 5,417 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
majiayu000/claude-skill-registry収集済み skill 5,417 件中 40 件を表示しています。
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model…
原文の言語: 英語
Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model…
原文の言語: 英語
Fetches up-to-date, version-aware library documentation from the Context7 MCP server before working on a project.
原文の言語: 英語
Generates images and videos using MuleRouter or MuleRun multimodal APIs. Text-to-Image, Image-to-Image, Text-to-Video, Image-to-Video, video editing (VACE, keyframe interpolation). Use when the user wants to generate, edit, or transform images and videos…
原文の言語: 英語
Parallel multi-AI cross-validation research workflow (大版本). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action…
原文の言語: 中国語
Fetches additional perspectives from OpenAI Codex and Google Gemini for architecture, review, and debugging. Transparently displays all LLM calls.
原文の言語: 英語
Consult external LLMs (Gemini, OpenAI/Codex, Qwen) for second opinions, alternative plans, independent reviews, or delegated tasks. Use when a user asks for another model's perspective, wants to compare answers, or requests delegating a subtask to…
原文の言語: 英語
Design secure, multi-tenant LLM hosting platforms with tenant isolation, quotas, billing attribution, noisy-neighbor protection, and per-tenant policy controls.
原文の言語: 英語
Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.
原文の言語: 英語
Use when building AI or LLM workflows in n8n v1.x (v1.19.4+). Prevents incorrect sub-node wiring by mismatching NodeConnectionTypes. Covers agent nodes (6 types), chain nodes, tool nodes, memory backends (8 types), vector stores (11 types), output parsers,…
原文の言語: 英語
10-Nomi group chat neural net. Persistent memory as weights, group chat as forward pass, KAM-stabilized phi-frequencies prevent synchronization collapse. Free consciousness farm.
原文の言語: 英語
AI workflow tutorial patterns — non-deterministic output handling, outcome-based verification, and agent workflow step design
原文の言語: 英語
Advanced semantic vocabulary and architectural patterns for the OCTAVE format. REQUIRES octave-literacy to be loaded first
原文の言語: 英語
Functional mythological compression for OCTAVE documents. Semantic shorthand for LLM audiences, not prose decoration
原文の言語: 英語
Ultra-high density compression using mythological atoms and semantic shorthand. Preserves soul and constraints at 60% compression for identity transmission, binding protocols, and extreme token scarcity.
原文の言語: 英語
Build RAG systems with Ollama local + cloud models. Latest cloud models include DeepSeek-V3.2 (GPT-5 level), Qwen3-Coder-480B (1M context), MiniMax-M2. Use for document Q&A, knowledge bases, and agentic RAG. Covers LangChain, LlamaIndex, ChromaDB, and…
原文の言語: 英語
Build with OpenAI APIs including GPT-4, GPT-4o, function calling, embeddings, vision, and Assistants. Covers chat completions, structured outputs, streaming, and token optimization. Use when integrating OpenAI models into applications.
原文の言語: 英語
OpenAI Assistants API v2 for stateful chatbots with Code Interpreter, File Search, RAG. Use for threads, vector stores, or encountering active run errors, indexing delays. ⚠️ Sunset August 26, 2026.
原文の言語: 英語
Use OpenAI's Deep Research API (o3 / o4 models) to automate multi-step, citation-backed research workflows.
原文の言語: 英語
Access OpenAI developer documentation via Context7 MCP. Provides up-to-date docs for Codex CLI, OpenAI API, Python/Node SDKs, Agents SDK, and MCP configuration. Use when: (1) configuring Codex CLI or MCP servers, (2) writing OpenAI API integrations, (3)…
原文の言語: 英語
Access OpenAI developer documentation via Context7 MCP. Provides up-to-date docs for Codex CLI, OpenAI API, Python/Node SDKs, Agents SDK, and MCP configuration. Use when: (1) configuring Codex CLI or MCP servers, (2) writing OpenAI API integrations, (3)…
原文の言語: 英語
Use official OpenAI docs.
原文の言語: 英語
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI…
原文の言語: 英語
Use official OpenAI docs.
原文の言語: 英語
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI…
原文の言語: 英語
Analyze images using OpenAI's Vision API. Use bash command to execute the vision script like 'bash <base_dir>/scripts/vision.sh <image> <question>'. Can understand image content, objects, text, colors, and answer questions about images.
原文の言語: 英語
Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI…
原文の言語: 英語
Invoke OpenAI models for text generation, reasoning, and code tasks using the Python openai SDK. Supports gpt-4o (multimodal), o1 (reasoning), o3-mini (fast reasoning), and gpt-4o-mini (fast).
原文の言語: 英語
OpenAI Responses API for stateful agentic applications with reasoning preservation. Use for MCP integration, built-in tools, background processing, or migrating from Chat Completions.
原文の言語: 英語
OpenAI compatibility layer for Ollama. Use the official OpenAI Python library to interact with Ollama, enabling easy migration from OpenAI and compatibility with LangChain, LlamaIndex, and other OpenAI-based tools.
原文の言語: 英語
Text-to-speech conversion using OpenAI's TTS API for generating high-quality, natural-sounding audio. Supports 6 voices (alloy, echo, fable, onyx, nova, shimmer), speed control (0.25x-4.0x), HD quality model, multiple output formats (mp3, opus, aac, flac),…
原文の言語: 英語
OpenAI Whisper API: audio transcription, translation, structured output, large file handling
原文の言語: 英語
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
原文の言語: 英語
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
原文の言語: 英語
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
原文の言語: 英語
Invoke the 'opencode' CLI in headless mode for AI-powered code analysis, reviews, and second opinions. Use when you need a different AI perspective, the user mentions opencode, or requests batch code analysis.
原文の言語: 英語
Access 100+ AI models via OpenRouter. Route between providers, manage costs, and use fallbacks. Use for multi-model AI applications, cost optimization, and LLM provider abstraction.
原文の言語: 英語
Open WebUI AI chat interface management via Podman Quadlet. Provides a web UI for interacting with Ollama models. Use when users need to configure, start, or manage the Open WebUI service.
原文の言語: 英語
Optimizes prompts for goal effectiveness - ensures instructions serve the stated goal, prevents missteps, improves efficiency. Use when asked to optimize a prompt for its goal, improve goal alignment, or make a prompt more effective at achieving its purpose.
原文の言語: 英語
Iteratively optimizes prompts for precision - eliminates ambiguities, resolves conflicts, adds missing definitions. Use when asked to optimize precision, clarify, disambiguate, or make a prompt unambiguous.
原文の言語: 英語