When facilitating sprint retrospectives or team improvement sessions.
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →When facilitating sprint retrospectives or team improvement sessions.
Comprehensive guide to Agile Scrum methodology including roles, ceremonies, artifacts, sprint planning, and best practices for iterative software development
Plan and execute effective sprints using Agile methodologies. Define sprint goals, estimate user stories, manage sprint backlog, and facilitate daily standups to maximize team productivity and deliver value incrementally.
Agile product management, Scrum practices, and team collaboration for iterative product development.
Quality Assurance & Design Validation Agent
<skill>
后端代码生成 Skill，负责在 SoT 约束下生成 FastAPI 后端代码。
<skill>
<skill>
<skill>
前端代码生成 Skill，负责在 SoT 约束下生成 Next.js/React 前端代码。
<skill>
<skill>
你是一个 **严格可控的 SoT 文档流水线执行器（Pipeline Runner）**：
<skill>
<skill>
测试用例生成 Skill，负责根据 SoT 文档和业务代码生成 pytest 测试用例。
Comprehensive L&D framework for upskilling DevOps/IaC/Automation teams to become AI Agent Engineers. Covers LLM literacy, RAG, agent frameworks, multi-agent systems, and LLMOps. Designed to help traditional automation teams compete with OpenAI and Anthropic.
Production-grade AI agent patterns with MCP integration, agentic RAG, handoff orchestration, multi-layer guardrails, observability, token economics, ROI frameworks, and build-vs-not decision guidance (modern best practices)
ai-app
AI-powered development tools configuration and usage
Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.
AI-powered issue operations via gh-models. TRIGGERS - issue summarization, auto-labeling, issue insights.
The AI Board is a sophisticated reasoning system that dynamically selects and combines advanced LLM techniques to achieve maximum accuracy on complex questions. It uses multi-agent debate, adversarial
- {'principle': 'Brand is encoded in prompts, not just documents', 'why': 'AI tools need actionable instructions, not passive PDFs. Every brand\nguideline must translate to reusable prompts that AI ca
AI-powered code generation for boilerplate, tests, data, and scaffolding
> **定位**: 独立的 AI 编程质量保障助手，重点关注代码质量提升和安全性
ai-collaborate-teaching
Design co-learning experiences using the Three Roles Framework (AI as Teacher/Student/Co-Worker). Use when teaching AI-driven development workflows, spec-first collaboration, or balancing AI assistance with foundational learning. NOT for curriculum without AI integration.
AI Collaboration Standards
> **语言**: [English](../../../../../skills/claude-code/ai-collaboration-standards/SKILL.md) | 简体中文
You are a specialized cross-validation assistant that uses Google's Gemini 2.5 Pro API to provide independent, multi-perspective code validation alongside Claude's analysis.
Fetches AI news from smol.ai RSS and generates structured markdown with intelligent summarization and categorization. Optionally creates beautiful HTML webpages with Apple-style themes and shareable card images. Use when user asks about AI news, daily tech updates, or wants news organized by date or category.
Synchronize and update Claude Code and GitHub Copilot development tool configurations to work similarly. Use when asked to update Claude Code setup, update Copilot setup, sync AI dev tools, add new skills/prompts/agents across both platforms, or ensure Claude and Copilot configurations are aligned. Covers skills, prompts, agents, instructions, workflows, and chat modes.
Use when deciding between HITL, OHOTL, and AHOTL modes in AI-DLC workflows. Covers decision frameworks for human involvement levels and mode transitions.
<skill>
shadcn/ui AI chat components for conversational interfaces. Use for streaming chat, tool/function displays, reasoning visualization, or encountering Next.js App Router setup, Tailwind v4 integration, AI SDK v5 migration errors.
Build production-ready LLM applications, advanced RAG systems, and
Navigating the regulatory landscape and ethical frameworks for responsible AI development and deployment.
Responsible AI development and ethical considerations. Use when evaluating
Help users create and run AI evaluations. Use when someone is building evals for LLM products, measuring model quality, creating test cases, designing rubrics, or trying to systematically measure AI output quality.
AI-powered insights, UX copywriting standards, and user experience guidelines for vehicle insurance platform. Use when designing insight panels, writing user-facing copy, implementing status messages, creating onboarding flows, or improving accessibility. Covers tone standards, interactive patterns, error messages, and empty states.
AI Instruction File Standards Guide
ai-instruction-standards
Integrate AI tools and APIs into business workflows and applications
ai-langchain4j
Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability.
Manage AI agents through the AI Maestro CLI. This skill provides commands for creating, updating, deleting, hibernating, and waking agents. It also handles plugin management and agent import/export.
End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining).
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).