GitHub
aws-agentcore
Build AI agents with AWS Bedrock AgentCore. Use when developing agents on AWS infrastructure, creating tool-use patterns, implementing agent orchestration, or integrating with Bedrock models. Triggers on keywor...
☆ 99查看技能
research llm ai AI 技能
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GitHub
aws-strands
Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands...
☆ 99查看技能
GitHub
council
Multi-agent debate system. USE WHEN council, debate, perspectives, agents discuss. SkillSearch('council') for docs.
☆ 99查看技能
GitHub
paiupgrade
Extract system improvements from content AND monitor external sources (Anthropic ecosystem, YouTube). USE WHEN upgrade, improve system, system upgrade, analyze for improvements, check Anthropic, Anthropic chang...
☆ 99查看技能
GitHub
research
Comprehensive research, analysis, and content extraction system. USE WHEN user says 'do research', 'do extensive research', 'quick research', 'minor research', 'research this', 'find information', 'investigate'...
☆ 99查看技能
GitHub
prompting
Meta-prompting system for dynamic prompt generation using templates, standards, and patterns. USE WHEN meta-prompting, template generation, prompt optimization, or programmatic prompt composition.
☆ 99查看技能
GitHub
thealgorithm
Universal execution engine using scientific method to achieve ideal state. USE WHEN complex tasks, multi-step work, "run the algorithm", "use the algorithm", OR any non-trivial request that benefits from struct...
☆ 99查看技能
GitHub
agents
Dynamic agent composition and management system. USE WHEN user says create custom agents, spin up custom agents, specialized agents, OR asks for agent personalities, available traits, agent voices. Handles cust...
☆ 99查看技能
GitHub
telos
Life OS and project analysis. USE WHEN TELOS, life goals, projects, dependencies, books, movies. SkillSearch('telos') for docs.
☆ 99查看技能
GitHub
core
Personal AI Infrastructure core. AUTO-LOADS at session start. The authoritative reference for how the PAI system works, how to use it, and all system-level configuration. USE WHEN any session begins, user asks...
☆ 99查看技能
GitHub
redteam
Adversarial analysis with 32 agents. USE WHEN red team, attack idea, counterarguments, critique, stress test. SkillSearch('redteam') for docs.
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GitHub
chunking-strategy
Implement optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require bre...
☆ 98查看技能
GitHub
prompt-engineering
This skill should be used when creating, optimizing, or implementing advanced prompt patterns including few-shot learning, chain-of-thought reasoning, prompt optimization workflows, template systems, and system...
☆ 98查看技能
GitHub
qdrant-vector-database-integration
Qdrant vector database integration patterns with LangChain4j. Store embeddings, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, sema...
☆ 98查看技能
GitHub
aws-sdk-java-v2-bedrock
Amazon Bedrock patterns using AWS SDK for Java 2.x. Use when working with foundation models (listing, invoking), text generation, image generation, embeddings, streaming responses, or integrating generative AI...
☆ 98查看技能
GitHub
langchain4j-rag-implementation-patterns
Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating...
☆ 98查看技能
GitHub
langchain4j-vector-stores-configuration
Configure LangChain4J vector stores for RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/...
☆ 98查看技能
GitHub
spring-ai-mcp-server-patterns
Model Context Protocol (MCP) server implementation patterns with Spring AI. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates using Spring's official AI...
☆ 98查看技能
GitHub
rag-implementation
Build Retrieval-Augmented Generation (RAG) systems for AI applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs...
☆ 98查看技能
GitHub
langchain4j-spring-boot-integration
Integration patterns for LangChain4j with Spring Boot. Auto-configuration, dependency injection, and Spring ecosystem integration. Use when embedding LangChain4j into Spring Boot applications.
☆ 98查看技能
GitHub
langchain4j-testing-strategies
Testing strategies for LangChain4j-powered applications. Mock LLM responses, test retrieval chains, and validate AI workflows. Use when testing AI-powered features reliably.
☆ 98查看技能
GitHub
langchain4j-mcp-server-patterns
Model Context Protocol (MCP) server implementation patterns with LangChain4j. Use when building MCP servers to extend AI capabilities with custom tools, resources, and prompt templates.
☆ 98查看技能
GitHub
langchain4j-tool-function-calling-patterns
Tool and function calling patterns with LangChain4j. Define tools, handle function calls, and integrate with LLM agents. Use when building agentic applications that interact with tools.
☆ 98查看技能
GitHub
langchain4j-ai-services-patterns
Build declarative AI Services with LangChain4j using interface-based patterns, annotations, memory management, tools integration, and advanced application patterns. Use when implementing type-safe AI-powered fe...
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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。