GitHub
proxy-mode-reference
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.
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tools llm ai AI 技能
发现 tools llm ai 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
分类目录: tools llm ai
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GitHub
sim-to-real
Provides guidelines and principles for bridging the gap between simulated robotics environments and real-world hardware deployment in Physical AI.
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GitHub
ros2-code-example-writer
Generate working Python/rclpy code examples for Physical AI & Humanoid Robotics textbook with tier-specific variants (Simulation/Jetson/Robot).
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GitHub
vla-patterns
Vision-Language-Action model integration patterns for cognitive robotics with ROS 2.
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GitHub
isaac-patterns
NVIDIA Isaac Sim and Isaac ROS integration patterns for Physical AI applications.
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GitHub
ros2-standards
Authoritative guidelines for writing production-grade ROS 2 (Humble) Python 3.11+ code (leveraging 3.12+ features where compatible) for Physical AI applications.
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GitHub
macos-say
Use macOS text-to-speech via the `say` command for voice feedback, audio narration, and spoken output.
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GitHub
questions
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.
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GitHub
agent-skill-templates
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.
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GitHub
subagent-patterns
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。
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GitHub
frontend-aesthetics
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...
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GitHub
evaluation
Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.
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GitHub
grounded-answer
Provide accurate, evidence-based answers by referencing sources from documents, textbooks, or research papers. Use when user asks for factual or source-backed responses.
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GitHub
extract-physical-ai-formulas
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.
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GitHub
summarize-robotics-text
Summarize robotics-related text, research papers, or lecture notes into concise, clear, and structured summaries. Use when user asks to condense or simplify robotics content.
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GitHub
learning-objective-generator
Generate clear, measurable, and curriculum-aligned learning objectives for any topic. Use when user asks to define goals, outcomes, or objectives for a lesson or course.
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GitHub
skill-creator
Create new Agent Skills with proper structure, templates, and best practices. Use when building custom skills for Claude Code, GitHub Copilot, or other Agent Skills-compatible tools.
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GitHub
doc-contents
Generate project documentation including CONTENTS.md navigation files and AGENTS.md instructions. Use when creating documentation structure, project indexes, or AI agent configuration files.
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GitHub
sentiment-analyzer
Analyze emotional tone, sentiment polarity, and psychological impact of text. Execute Python script for detailed sentiment analysis. Use when analyzing mood, attitude, or emotional content.
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GitHub
text-analyzer
Comprehensive text analysis coordinator. Execute Python script for multi-aspect text analysis. Use when you need grammar, sentiment, readability, and SEO analysis combined.
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GitHub
spec-and-plan-generation
This skill should be used when commands need to generate specifications or implementation plans, when the user asks about "how to write specs", "how to create plans", "spec structure", "plan hierarchy", or when...
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GitHub
conductor-methodology
This skill should be used when the user asks about "conductor methodology", "context-driven development", "conductor directory structure", "conductor files", "tracks.md", "plan.md", "spec.md", or when commands...
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GitHub
ml-engineer
Implement ML pipelines, model serving, and feature engineering. Handles TensorFlow/PyTorch deployment, A/B testing, and monitoring. Use PROACTIVELY for ML model integration or production deployment.
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GitHub
mlops-engineer
Build ML pipelines, experiment tracking, and model registries. Implements MLflow, Kubeflow, and automated retraining. Handles data versioning and reproducibility. Use PROACTIVELY for ML infrastructure, experime...
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默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。