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。
Create high-quality, progressive learning tutorials for VRP Toolkit. Use when the user requests creating tutorials, educational content, or learning materials for any VRP toolkit feature (problem creation, algo...
Systematic workflow and API reference for integrating Streamlit playground with vrp-toolkit modules. Use when developing playground features, connecting UI to vrp-toolkit APIs, or encountering API signature mis...
Research academic papers and questions, write typst documents with cetz visualizations, teach until human understands
Generate comprehensive agents.md files for Builder.io Fusion projects. Creates project-specific AI instruction files that establish conventions, build commands, testing procedures, design system rules, and codi...
获取最新的AI行业新闻，进行智能总结和筛选，最多展示10条最重要的新闻资讯。当用户需要了解AI行业最新动态时使用此skill。
自动从网络收集 Claude Code 的最新使用技巧、功能更新和最佳实践。当用户需要了解 Claude Code 的新功能、使用技巧、高级用法或 Claude Agent SDK 开发时使用此skill。支持本地缓存，避免重复搜索。
Use this skill when implementing complex programming tasks that benefit from multi-agent collaboration. This skill coordinates a Master LLM (orchestrator) with specialized agents (Requirements Agent, Code Agent...
Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledg...
Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building d...
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems,...
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cogn...
Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill...
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intell...
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, impleme...
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination,...
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling t...
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learnin...
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
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。