book-ingestion
Generate the complete RAG ingestion script to crawl textbook from sitemap.xml, chunk content, embed using Gemini, and push to Qdrant following MCP documentation.
Generate the complete RAG ingestion script to crawl textbook from sitemap.xml, chunk content, embed using Gemini, and push to Qdrant following MCP documentation.
Standardize AskUserQuestion patterns and provide reusable question templates for batch optimization
Ensures questions are answered literally before taking action. Triggers on user input containing '?' or patterns like 'why did you...?', 'will that work?', 'have you considered...?'. Use when user asks about your decisions, challenges an approach, or requests assessment. Prevents interpreting questions as implicit instructions or criticism.
Create and configure Claude Code hooks for customizing agent behavior. Use when the user wants to (1) create a new hook, (2) configure automatic formatting, logging, or notifications, (3) add file protection or custom permissions, (4) set up pre/post tool execution actions, or (5) asks about hook events like PreToolUse, PostToolUse, Notification, etc.
Instrument RAG retrieval, memory operations, and context management
Build AI agents with Hugging Face's SmolAgents framework. Use when creating code-executing agents, tool-calling agents, multi-agent systems, agentic RAG, text-to-SQL pipelines, web browsing agents, or any multi-step AI workflows. Covers CodeAgent, ToolCallingAgent, custom tools, MCP integration, memory management, secure code execution (E2B, Docker, Blaxel), and model configuration (HF Inference, LiteLLM, Transformers, Ollama).
Generate images from text prompts using fal.ai Gemini 3 Pro. Use when the user asks to create, generate, or make an image from a text description. Supports multiple aspect ratios and resolutions up to 4K.
Ecology for developing ideas through concept exploration, research, and implementation. ACTIVATE for dev work: - "what's next for [app]", "continue [app]", "work on [app]" - "build [feature]", "implement [feature]", "plan the iteration" - "read the implementation notes", "what's the iteration status" - "what should I build next", "next steps for [project]" ACTIVATE for concept work: - "explore [concept]", "go deeper into [idea]", "where am I", "what's here" - "capture this thought", "hold this", "note this" - "test through ecology", "compare these", "attune [quality]" ACTIVATE for research: - "start research on [topic]", "investigate [question]", "begin inquiry" ACTIVATE when in qino workspace (has .claude/qino-config.json). NOT implicit: arc capture requires explicit invocation ("/qino arc" or "capture an arc").
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Use when building "MCP server", "Model Context Protocol", creating "Claude tools", "MCP tools", or asking about "FastMCP", "MCP SDK", "tool development for LLMs", "external API integration for Claude"
LLM integration patterns for building AI-powered applications with Anthropic Claude and OpenAI APIs. Use when integrating Claude or OpenAI APIs, implementing chat features, adding streaming responses, managing multi-turn conversations, implementing prompt engineering, tracking LLM costs, handling rate limits, or building AI-powered features. Includes client setup, error handling, and cost optimization.
AIOS Agent Operating System and Cerebrum SDK for building, deploying, and orchestrating AI agents
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
ChatBotプロジェクトの開発全般を支援するスキル。プロジェクト構造、コーディング規約、開発ワークフローに関する知識を提供します。ChatBotプロジェクトで作業する時、プロジェクト構造について質問された時、コーディング規約について質問された時、新しい機能を追加する時に使用してください。
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Outline the lightweight process for turning discovery inputs into a first-draft Sentient proposal.
Plan and execute an evidence-first interrogation using approved probes; outputs schema-valid findings + report.
Deep reasoning framework for complex tasks with confidence validation, context gathering, and systematic planning