Build production LangChain agents with create_agent(), tools, and middleware patterns. \n \n Use create_agent() with model, tools list, and system prompt; co…
Find, trial, compare, and govern AI agents before hiring
Data
Connect APIs, databases, warehouses, spreadsheets, analytics, and ETL workflows.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Connect a dataset or API to a reusable analysis workflow.
- Evaluate extraction, transformation, and retrieval candidates.
Sandbox-first next steps
Data candidates
Showing 12 of 4771. Adjust filters to narrow the review list without losing job context.
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.
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This skill helps you plan and execute LangChain migrations with phased strategies, tooling, and validation to minimize risk.
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This skill helps you master production-grade LangChain orchestration across chains, agents, memory, and RAG patterns for scalable LLM applications.
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ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph agent building project. Required starting point before choosing other skills or writing any…
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This skill helps you build robust LangChain applications by guiding chains, agents, memory, and RAG patterns across production-ready components.
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This skill helps you validate and approve LangChain production readiness by guiding configuration, observability, security, and deployment checks.
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This skill helps design production-ready LangChain architectures with scalable patterns, provider abstraction, and chain management for enterprise LLM
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This skill helps you implement LangChain security best practices from secrets management to prompt protection for safe production usage.
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This skill provides a concise LangChain 1.0 quick reference for building agents, tools, memory, and middleware workflows.
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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".
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This skill helps you build declarative, type-safe AI services with LangChain4j in Java, enabling memory, tool integration, and structured outputs.
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Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
4771 candidates for Data. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.