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Found 82 Skills
Implement LangChain rate limiting and backoff strategies. Use when handling API quotas, implementing retry logic, or optimizing request throughput for LLM providers. Trigger with phrases like "langchain rate limit", "langchain throttling", "langchain backoff", "langchain retry", "API quota".
Configure LangChain local development workflow with hot reload and testing. Use when setting up development environment, configuring test fixtures, or establishing a rapid iteration workflow for LangChain apps. Trigger with phrases like "langchain dev setup", "langchain local development", "langchain testing", "langchain development workflow".
Complex migration strategies for LangChain applications. Use when migrating from legacy LLM frameworks, refactoring large codebases, or implementing phased migration approaches. Trigger with phrases like "langchain migration strategy", "migrate to langchain", "langchain refactor", "legacy LLM migration", "langchain transition".
Apply production-ready LangChain SDK patterns for chains, agents, and memory. Use when implementing LangChain integrations, refactoring code, or establishing team coding standards for LangChain applications. Trigger with phrases like "langchain SDK patterns", "langchain best practices", "langchain code patterns", "idiomatic langchain", "langchain architecture".
AI agent development standards using golanggraph for graph-based workflows, langchaingo for LLM calls, tool integration, MCP, and LLM best practices (context compression, prompt caching, attention raising, tool response trimming).
Use this skill for ANY question about creating test or evaluation datasets for LangChain agents. Covers generating datasets from traces (final_response, single_step, trajectory, RAG types), uploading to LangSmith, and managing evaluation data.
Use when adding LangChain-based LLM routes or services in Python or Next.js stacks; pair with architect-stack-selector.
Integrate PICA into a LangChain/LangGraph Python application via MCP. Use when adding PICA tools to a LangChain agent, setting up PICA MCP with LangChain, or when the user mentions PICA with LangChain or LangGraph.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
Master enterprise-grade TypeScript development with type-safe patterns, modern tooling, and framework integration. This skill provides comprehensive guidance for TypeScript 5.9+, covering type system fundamentals (generics, mapped types, conditional types, satisfies operator), enterprise patterns (error handling, validation with Zod), React integration for type-safe frontends, NestJS for scalable APIs, and LangChain.js for AI applications. Use when building type-safe applications, migrating JavaScript codebases, configuring modern toolchains (Vite 7, pnpm, ESLint, Vitest), implementing advanced type patterns, or comparing TypeScript with Java/Python approaches.
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
Add email capabilities to AI agents using popular frameworks. Provides pre-built tools for TypeScript and Python frameworks including Vercel AI SDK, LangChain, Clawdbot, OpenAI Agents SDK, and LiveKit Agents. Use when integrating AgentMail with agent frameworks that need email send/receive tools.