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Transform user requests into detailed, precise prompts for AI models. Use when users say "promptify", "promptify this", or explicitly request prompt engineering or improvement of their request for better AI res...
Generate lorem ipsum placeholder text. This skill should be used when users ask to generate lorem ipsum content, placeholder text, dummy text, or filler text. Supports various structures including plain paragra...
Generate and edit images using Google's Nano Banana Pro (Gemini 3 Pro Image) API. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an exis...
Google API Improvement Proposals (AIP) reference. Use BEFORE designing or reviewing APIs, protobuf definitions, or any work involving Google API design standards. Fetches relevant AIP rules from https://google....
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or to...
构建高质量 MCP（模型上下文协议）服务器的指南，使 LLM 能够通过精心设计的工具与外部服务交互。在使用 Python (FastMCP) 或 Node/TypeScript (MCP SDK) 构建 MCP 服务器以集成外部 API 或服务时使用。
创建高效技能的指南。当用户想要创建新技能（或更新现有技能）以扩展 Claude 的能力，包括专业知识、工作流程或工具集成时，应使用此技能。
Analyzes Claude Code conversation JSONL files to extract structured data and generate problem-solution narratives for semantic search indexing
Multi-LLM deliberation framework for strategic decisions through pressure-based expert consultation
Writes webnovel chapters (3000-5000 words) using v5.1 dual-agent architecture. Context Agent gathers context, writer produces pure text (no XML tags), review agents report issues, polish fixes problems, Data Ag...
Queries project settings for characters, powers, factions, items, and foreshadowing. Supports urgency analysis and golden finger status. Activates when user asks about story elements or /webnovel-query.
Load and review Emergent Learning Framework context, institutional knowledge, golden rules, and recent session history. Runs the checkin workflow interactively with banner, context loading, and dashboard/multi-...
Natural language search through Claude Code session history. Search for previous prompts, conversations, topics, file modifications, and context from past sessions. Useful for finding earlier work and understan...
Coordinate multi-agent orchestration for complex tasks. Launch parallel and sequential agents, manage dependencies, aggregate results, and orchestrate sophisticated workflows. Use for tasks requiring multiple s...
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.
Native multi-agent orchestration using Claude Code's Agent Tool. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Manages temporary and defined agents including creation, promotion, cleanup, and namespacing. Use when user creates custom agents, asks about agent lifecycle, temp agents, or agent management.
Use when user has complex multi-agent workflows, needs to coordinate sequential or parallel agent execution, wants workflow visualization and control, or mentions automating repetitive multi-agent processes - g...
Use when user describes complex multi-step tasks that could benefit from orchestration - guides natural language workflow creation
Use when user says "create workflow", "create a workflow", "design workflow", "orchestrate", "automate multiple steps", "coordinate agents", "multi-agent workflow". Creates orchestration workflows from natural...
Gemini CLI delegation workflow implementing delegation-core for Google's Gemini models.
Qwen CLI delegation workflow implementing delegation-core for Alibaba's Qwen models.
Delegate tasks to external LLM services (Gemini, Qwen) with quota, logging, and error handling.
Create and manage a Notion-based tweet performance tracking system for "poor man's reinforcement learning"
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.