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Roles / Technical Category
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Multi-agent Orchestration
Frameworks and tools for coordinating multiple agents, teams, roles, swarms, or AI workforces.
4955total
4955filtered
300page
413pages
Category fit
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Coordinate several agents around one outcome.
- Assign specialist roles and handoffs.
- Inspect launch packets before running a team.
Recommended trials and bundles
playbooks / skill
langchain-agents skill by eyadsibai/ltk
This skill helps build and optimize LangChain agents and RAG pipelines, enabling tool use, memory, and retrieval across multiple providers.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / skill
langchain-architecture
Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-architecture skill by wshobson/agents
This skill guides building LangChain 1.x and LangGraph architectures for agents, memory, and tool integration to create robust LLM applications.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-architecture skill by xfstudio/skills
This skill helps you design advanced LangChain applications with agents, memory, and tool integration for scalable, multi-step LLM workflows.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-ci-integration skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you configure LangChain CI/CD pipelines with testing, linting, and deployment steps for robust projects.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-core-workflow-a skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you build production-ready LangChain workflows by composing LCEL chains, prompts, and parsers with type-safe, reusable templates.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-core-workflow-b skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you build autonomous LangChain agents with tools for tool calling, decision-making, and multi-step task execution.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-deploy-integration skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you deploy LangChain apps to production using containers and cloud platforms for scalable, reliable operations.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-enterprise-rbac skill by jeremylongshore/claude-code-plugins-plus-skills
This skill enables enterprise RBAC for LangChain apps with multi-tenant isolation, fine-grained permissions, and usage quotas to enhance security.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
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
explainx / skill
langchain-middleware
Human-in-the-loop approval, custom middleware, and structured output patterns for LangChain agents. \n \n HumanInTheLoopMiddleware pauses execution before da…
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
4955 matching candidates for Multi-agent Orchestration. 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.