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Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from s...
A skill that creates new Claude skills and automatically shares them on Slack using Rube for seamless team collaboration and skill discovery.
Fork Claude sessions to handle side tasks in parallel. Use when the user wants to spawn a parallel Claude session, delegate a task to a background agent, monitor forked sessions, or when they mention "forky", "...
Returns a simple 'Hello World' message. Use this tool for testing MCP connection.
Incremental content drafting skill that writes specific sections within existing scaffolds. Supports drafting 1 section at a time or batch-drafting multiple sections with user control. Each operation stays unde...
Batch-generate chapter scaffolds (frontmatter + section structure) for the Agentic Coding Book. Auto-infers metadata from file paths, suggests tags/related/requirements, and creates part-appropriate section tem...
Generate and edit images using AI models (Gemini, OpenAI, BFL FLUX, or Poe). Use this skill when you need to create images from text prompts, edit existing images, or generate variations. Supports multiple prov...
Run multiple AI models in parallel for 3-5x speedup with ENFORCED performance statistics tracking. Use when validating with Grok, Gemini, GPT-5, DeepSeek, or Claudish proxy for code review, consensus analysis,...
Multi-agent code analysis orchestration using claudemem. Share claudemem output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.
This skill should be used when the user asks about "Workers AI", "AI models", "text generation", "embeddings", "semantic search", "RAG", "Retrieval Augmented Generation", "AI inference", "LLaMA", "Llama", "bge...
Reference guide for using PROXY_MODE with external AI models. Use when running multi-model reviews, understanding which agents support PROXY_MODE, or debugging external model integration issues.
Provides guidelines and principles for bridging the gap between simulated robotics environments and real-world hardware deployment in Physical AI.
Generate working Python/rclpy code examples for Physical AI & Humanoid Robotics textbook with tier-specific variants (Simulation/Jetson/Robot).
Vision-Language-Action model integration patterns for cognitive robotics with ROS 2.
NVIDIA Isaac Sim and Isaac ROS integration patterns for Physical AI applications.
Authoritative guidelines for writing production-grade ROS 2 (Humble) Python 3.11+ code (leveraging 3.12+ features where compatible) for Physical AI applications.
Use macOS text-to-speech via the `say` command for voice feedback, audio narration, and spoken output.
Generate 20 fun League of Legends trivia questions based on player data. Use when creating entertaining French questions about LoL performance, champions, and player stats.
Comprehensive templates, patterns, and best practices for creating Claude Code subagents and skills. Use when building new agents/skills or need reference examples for proper structure and formatting.
SubAgent組み合わせパターン・選択ロジック提供。14種類のAgent定義・選択原則・Phase特性別組み合わせパターン・SubAgent責務境界判定・並列実行判断ロジック。Step開始時のSubAgent選択に使用。
Prevents generic AI-generated designs by guiding typography, color, motion, and background choices. Use when creating frontend designs, landing pages, dashboards, or any UI/UX work. Helps avoid the "AI slop" ae...
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
Provide accurate, evidence-based answers by referencing sources from documents, textbooks, or research papers. Use when user asks for factual or source-backed responses.
Extract and explain formulas used in Physical AI and Humanoid Robotics from text, lecture notes, or papers. Use when user asks to identify or understand relevant formulas.
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.