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Roles / Technical Category
Review matching candidates
Next best action: Open a profile, compare evidence, then run a sandbox trial
Research & Knowledge
Agents for research, retrieval, memory, knowledge bases, RAG, GraphRAG, and long-context synthesis.
4677total
4677filtered
282page
390pages
Category fit
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Collect and synthesize source-backed research.
- Build reusable knowledge assets.
- Preserve citations and assumptions for review.
Recommended trials and bundles
explainx / skill
langchain-fundamentals
Build production LangChain agents with create_agent(), tools, and middleware patterns. \n \n Use create_agent() with model, tools list, and system prompt; co…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-js skill by mgd34msu/goodvibes-plugin
Builds LLM-powered applications with LangChain.js for chat, agents, and RAG. Use when creating AI applications with chains, memory, tools, and retrieval-augmented generation in JavaScript.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-migration-deep-dive skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you plan and execute LangChain migrations with phased strategies, tooling, and validation to minimize risk.
MCPCLISDK
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-orchestration skill by manutej/luxor-claude-marketplace
This skill helps you master production-grade LangChain orchestration across chains, agents, memory, and RAG patterns for scalable LLM applications.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
mcpservers / skill
langchain-oss-primer
ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-patterns skill by amnadtaowsoam/cerebraskills
This skill helps you build robust LangChain applications by guiding chains, agents, memory, and RAG patterns across production-ready components.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-prod-checklist skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you validate and approve LangChain production readiness by guiding configuration, observability, security, and deployment checks.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-reference-architecture skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps design production-ready LangChain architectures with scalable patterns, provider abstraction, and chain management for enterprise LLM
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-security-basics skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you implement LangChain security best practices from secrets management to prompt protection for safe production usage.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-use-skill skill by nanmicoder/claude-code-skills
This skill provides a concise LangChain 1.0 quick reference for building agents, tools, memory, and middleware workflows.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-workflow-builder skill by patricio0312rev/skills
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain4j-ai-services-patterns skill by giuseppe-trisciuoglio/developer-kit
This skill helps you build declarative, type-safe AI services with LangChain4j in Java, enabling memory, tool integration, and structured outputs.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review support
Open Category guide
Review links
Technical category pages stay focused on job browsing; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
Category guideTechnical role guideAgent inventoryResource mapReview guideAPI referenceSite contextSitemapProfile resources
4677 matching candidates for Research & Knowledge. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role categoryOpen the focused review record
- 03Agent inventoryBrowse the matching inventory
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-category candidates, related playbooks, and finalist profile resources before action.
Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.