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探索开发、内容、数据与办公效率等 AI 技能。先比较用途和仓库热度,再查看技能说明与来源。

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显示第 865–888 个,共 96,528 个

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GitHub

handoff

steveyegge

Hand off to a fresh Claude session. Use when context is full, you've finished a logical chunk of work, or need a fresh perspective. Work continues from hook.

GitHub

agent-browser

slopus

Browser automation CLI for AI agents. Use this when asked to test something in a real browser.

GitHub

update-pipeline

dotnet

Implementation details for EF Core SaveChanges and the update pipeline. Use when changing CommandBatchPreparer, UpdateSqlGenerator, ModificationCommand, or related classes.

GitHub

agentdb-vector-search

ruvnet

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...

GitHub

v3-mcp-optimization

ruvnet

MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.

GitHub

hooks-automation

ruvnet

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,...

GitHub

hive-mind-advanced

ruvnet

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

GitHub

sparc-methodology

ruvnet

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

GitHub

v3-memory-unification

ruvnet

Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).

GitHub

v3-ddd-architecture

ruvnet

Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.

GitHub

agentic-jujutsu

ruvnet

Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

GitHub

agentdb-advanced-features

ruvnet

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,...

GitHub

github-multi-repo

ruvnet

Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration

GitHub

agentdb-learning-plugins

ruvnet

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...

GitHub

reasoningbank-intelligence

ruvnet

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...

GitHub

verification-quality-assurance

ruvnet

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

GitHub

v3-performance-optimization

ruvnet

Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.

GitHub

agentdb-performance-optimization

ruvnet

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...

GitHub

v3-core-implementation

ruvnet

Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.

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。

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