发现 devops 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。
Proactive token budget assessment and task chunking strategy. Use this skill when queries involve multiple large file uploads, requests for comprehensive multi-document analysis, complex multi-step workflows wi...
Analyzes skill usage patterns across conversations to track token consumption, identify heavy vs. lightweight skills, measure invocation frequency, detect co-occurrence patterns, and suggest consolidation oppor...
Conversational guidance for building software with AI agents, covering workflows, tool selection, prompt strategies, parallel agent management, and best practices based on real-world high-volume agentic develop...
Comprehensive guide for AI-assisted vibe coding. Use when the user wants to build applications through natural language prompts using tools like Lovable, Cursor, Replit, or Bolt. Includes best practices, pitfal...
Recognize and capture reusable patterns, workflows, and domain knowledge from work sessions into new skills. Use when completing tasks that involve novel approaches repeated 2+ times, synthesizing complex domai...
Debug, diagnose, and troubleshoot skill issues including trigger failures, parameter problems, prompt conflicts, and SKILL.md structural issues. Use when skills don't activate as expected, trigger incorrectly,...
Transform reading notes and insights into polished, authentic content (blogs, social media, visualizations) that preserves your unique voice and avoids AI-style writing. Creates content that sounds unmistakably...
Comprehensive framework for evaluating AI vendors and solutions to avoid costly mistakes. Use this skill when assessing AI vendor proposals, conducting due diligence, evaluating contracts, comparing vendors, or...
Analyzes skill ecosystem to visualize dependencies, identify workflow bottlenecks, and recommend optimal skill stacks. Use when asked about skill combinations, workflow optimization, bottleneck identification,...
Comprehensive library of proven prompting patterns, frameworks, and examples for different use cases. This skill should be used when creating prompting guides, analyzing prompt effectiveness, teaching prompting...
Use when Claude Code needs a second opinion, verification, or deeper research on technical matters. This includes researching how a library or API works, confirming implementation approaches, verifying technica...
Guides architects on when and how to use goal-seeking agents as a design pattern. This skill helps evaluate whether autonomous agents are appropriate for a given problem, how to structure their objectives, inte...
Generates agentic outside-in tests using gadugi-agentic-test framework for CLI, TUI, Web, and Electron apps. Use when you need behavior-driven tests that verify external interfaces without internal implementati...
Proactive context window management via token monitoring, intelligent extraction, and selective rehydration. Features predictive budget monitoring, context health indicators, and priority-based retention. Use w...
Creates personalized learning paths for technologies, frameworks, or concepts. Use for user-interactive session only for onboarding new technologies, hackathon skill-building, or personal development planning....
Cross-session learning system that extracts insights from session transcripts and injects relevant past learnings at session start. Uses simple keyword matching for relevance. Complements DISCOVERIES.md/PATTERN...
Automated reproduction of comprehensive model evaluation benchmarks following the Benchmark Suite V3. Auto-activates for model benchmarking, comparison evaluation, or performance testing between AI models.
Conversational interface for managing MCP (Model Context Protocol) server configurations in Claude Code
Performs quick research using web search and synthesis when user asks about unfamiliar topics, new technologies, or needs current information. Activates on questions like 'how does X work', 'what is Y', or when...
Track and report agent invocation metrics including usage counts, success/failure rates, and completion times. Use for understanding which agents are utilized, identifying underused agents, and optimizing agent...
Proactive context window management via token monitoring, intelligent extraction, and selective rehydration. Use when approaching token limits or needing to preserve essential context. Complements /transcripts...
Comprehensive knowledge of Microsoft Agent Framework for building production AI agents and workflows. Auto-activates for agent building, workflow design, AutoGen migration, and enterprise AI tasks.
Expert delegation specialist that creates comprehensive context packages for coding agents, analyzes requirements, identifies relevant files, and generates clear instructions. Activates when delegating work, as...
Extracts key learnings from conversations, debugging sessions, and failed attempts. Use at session end or after solving complex problems to capture insights. Stores discoveries in memory (via amplihack.memory.d...
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。