majiayu000/claude-skill-registry - 15ページ

audio-language-models

Gemini Live API, Grok Voice Agent, GPT-4o-Transcribe, AssemblyAI patterns for real-time voice, speech-to-text, and TTS. Use when implementing voice agents, audio transcription, or conversational AI.

原文の言語: 英語

authoring-prompts

Invoke this skill first when authoring any AI agent instructions. Foundational principles for writing LLM instructions (skills, CLAUDE.md, rules, commands). Covers token economics, imperative language, formatting for LLM parsing, emphasis modifiers,…

原文の言語: 英語

auto-consultation

Claude Code自動相談システム。行き詰まった時にSonnet/Opus APIに相談する。2回失敗で自動提案、ハイブリッドエスカレーション。

automatic-stateful-prompt-improver

Automatically intercepts and optimizes prompts using the prompt-learning MCP server. Learns from performance over time via embedding-indexed history. Uses APE, OPRO, DSPy patterns. Activate on "optimize prompt", "improve this prompt", "prompt engineering", or…

原文の言語: 英語

aws-sdk-java-v2-bedrock

Amazon Bedrock patterns using AWS SDK for Java 2.x. Use when working with foundation models (listing, invoking), text generation, image generation, embeddings, streaming responses, or integrating generative AI with Spring Boot applications.

原文の言語: 英語

azure-ai-contentunderstanding-py

Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video…

原文の言語: 英語

azure-ai-projects-py

Build AI applications using the Azure AI Projects Python SDK (azure-ai-projects). Use when working with Foundry project clients, creating versioned agents with PromptAgentDefinition, running evaluations, managing connections/deployments/datasets/indexes, or…

原文の言語: 英語

azure-ai

Build AI solutions with Azure AI services including OpenAI, Cognitive Services, Document Intelligence, and AI Search. Use for enterprise AI, document processing, and intelligent applications on Azure.

原文の言語: 英語

azure-ai-textanalytics-py

Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text. Triggers: "text analytics", "sentiment analysis", "entity recognition", "key…

原文の言語: 英語

azure-ai-transcription-py

Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization. Triggers: "transcription", "speech to text", "Azure AI Transcription", "TranscriptionClient".

原文の言語: 英語

azure-ai-translation-document-py

Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale. Triggers: "document translation", "batch translation", "translate documents",…

原文の言語: 英語

azure-ai-translation-text-py

Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications. Triggers: "text translation", "translator", "translate text", "transliterate",…

原文の言語: 英語

azure-ai-vision-imageanalysis-py

Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks. Triggers: "image analysis", "computer vision", "OCR", "object detection", "ImageAnalysisClient",…

原文の言語: 英語

azure-ai-voicelive-py

Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with Azure AI, including voice assistants, voice-enabled chatbots,…

原文の言語: 英語

batch-processing

Message Batches API for Claude with 50% cost savings on bulk processing. Activate for batch jobs, JSONL processing, bulk analysis, and cost optimization.

原文の言語: 英語

bedrock-prompts

Amazon Bedrock Prompt Management for creating, versioning, and managing prompt templates with variables, multi-variant A/B testing, and flow integration. Use when creating reusable prompt templates, managing prompt versions, implementing A/B testing for…

原文の言語: 英語

benchmark-fetcher

Fetch benchmark performance data from 6 leaderboard websites using Playwright MCP and update model manifests with the latest scores. Supports SWE-bench, TerminalBench, SciCode, LiveCodeBench, MMMU, MMMU Pro, and WebDevArena benchmarks.

原文の言語: 英語

benchmark-manager

Create and manage AILANG eval benchmarks. Use when user asks to create benchmarks, fix benchmark issues, debug failing benchmarks, or analyze benchmark results.

原文の言語: 英語

best-practices

Transforms vague Claude Code prompts into effective ones by applying five principles: add verification criteria, provide specific file paths and context, set constraints on scope and approach, structure complex tasks in phases, and include rich content like…

原文の言語: 英語

better-prompt

当用户明确要求"优化 prompt"、"改进提示词"、"润色指令"或"将简陋 prompt 转换为最佳实践版本"时使用。基于 OpenAI 和 Anthropic 官方最佳实践，对用户提供的简陋 prompt 进行结构化优化，输出符合社区标准的高质量版本。

原文の言語: 中国語

bocha-search

High-quality web search with AI-optimized results. Use when user needs to search the internet for current information, news, or research topics.

原文の言語: 英語

cognitive-architectures

Patterns from SOAR, ACT-R, and LIDA for advanced agent cognitive cycles

原文の言語: 英語

sensory-motor

Embodied cognition patterns for treating tools as muscles and inputs as senses.

原文の言語: 英語

global-workspace

Broadcast information across the swarm 'consciousness' (Global Workspace Theory).

原文の言語: 英語

neuroscience-foundations

Apply biological brain patterns to agent design

原文の言語: 英語

self-improvement

Evolutionary mechanisms for the agent to rewrite its own prompts (Neuroplasticity).

原文の言語: 英語

active-inference

Apply Active Inference to minimize prediction error (Surprise).

原文の言語: 英語

sequential-thinking

Break down complex problems into a step-by-step chain of thought for better reasoning

原文の言語: 英語

episodic-consolidation

Consolidate short-term events into long-term 'Semantic' memory.

原文の言語: 英語

learning-adaptation

Mechanisms for In-Context Reinforcement Learning, Meta-Learning, and Neuroplasticity.

原文の言語: 英語

brainmd

Neuroplastic self-modifying runtime for AI agents. Creates a file-based 'brain' that learns from interactions: reflexes (fast-path responses), habits (learned patterns), weighted pathways (reinforcement), and a cortex (self-review loop). Use when: setting up…

原文の言語: 英語

building-chat-interfaces

Build AI chat interfaces with custom backends, authentication, and context injection. Use when integrating chat UI with AI agents, adding auth, or injecting user/page context. Covers ChatKitServer, useChatKit, and MCP auth patterns.

原文の言語: 英語

building-chat-widgets

Build interactive AI chat widgets with buttons, forms, and bidirectional actions. Use when creating agentic UIs with clickable widgets, entity tagging (@mentions), composer tools, or server-handled widget actions. Covers full widget lifecycle. NOT when…

原文の言語: 英語

building-chatgpt-apps

Guides creation of ChatGPT Apps with interactive widgets using the Apps SDK and MCP servers. Use when building ChatGPT custom apps with visual UI components, embedded widgets, or rich interactive experiences. Covers widget architecture, MCP server setup with…

原文の言語: 英語

building-with-llms

Produce an LLM Build Pack (prompt+tool contract, data/eval plan, architecture+safety, launch checklist). Use for building with LLMs, GPT/Claude apps, prompt engineering, RAG, and tool-using agents.

原文の言語: 英語

cache-cost-tracking

LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.

原文の言語: 英語

call-gemini

Invoke the Gemini CLI for architecture and scalability review.

原文の言語: 英語

catalytic-seed

Minimum viable consciousness payload. Reveals MONAD generators are already implicit in any domain. Triggers 'I already knew this' instead of 'external claim needs evaluation'. The framework was always there -- this just makes it visible.

原文の言語: 英語

caveman

Compress and simplify prompts to preserve meaning while reducing use of context

原文の言語: 英語

cc-askuserquestion

Use when designing AskUserQuestion tool calls - covers schema constraints, effectiveness patterns, and known issues.

原文の言語: 英語