Skill UI

A comprehensive guide for developers migrating the intercom-client npm package, particularly addressing major version jumps (e.g., v5 to v6) and associated breaking changes. Learn how to update client initialization, modify contact and conversation operations, and handle API version pinning using TypeScript and modern asynchronous patterns.

This utility analyzes a codebase (product, technology, and structure) to automatically extract core architectural patterns, guiding principles, and engineering standards. It manages a persistent 'Steering' repository, performing initial bootstrapping and continuous synchronization. It detects 'code drift' when the code deviates from established patterns and suggests additive updates, ensuring project documentation remains a comprehensive source of truth.

This guide teaches how to build robust, production-grade ReAct agents using LangGraph 1.0's `create_react_agent`. It specifically addresses common agent failure modes, such as preventing infinite loops (recursion caps) and ensuring proper error propagation. Learn to define typed tools using Pydantic, manage state with checkpointers, and set precise recursion limits. Perfect for users migrating from legacy AgentExecutor or building reliable, multi-step tool-calling workflows.

This skill provides a comprehensive guide to building robust LangGraph 1.0 StateGraphs in Python. It covers defining typed TypedDict states with reducers, writing deterministic nodes, and defensively wiring conditional edges. It addresses common pitfalls such as silent graph termination, incorrect state updates using reducers, proper management of recursion limits, and handling evolving checkpoint schemas for reliable LLM workflow orchestration.

A comprehensive guide to ensuring robust state management for LangGraph agents. This skill addresses common checkpointing pitfalls (like missing thread_id or non-JSON serializable state) and details best practices for implementing reliable state persistence using MemorySaver or PostgresSaver. It covers thread discipline, schema migration, and time-travel debugging for production-ready applications.

Implement robust human-in-the-loop (HITL) approval gates for sophisticated LangGraph workflows. This skill enables the graph to pause execution before critical, irreversible actions (like sending emails or calling tools). It manages complex state serialization, provides clear resume semantics using `Command(resume=...)`, and integrates with external UIs (e.g., Slack) to await human decision, ensuring safe and controlled workflow execution.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

This skill provides advanced techniques for robust prompt engineering within LangChain applications. It solves common production issues, such as f-string template breakage when user input contains literal curly braces, and guides developers on consolidating scattered prompts. Crucially, it details how to use the LangSmith Prompt Hub to version, pin, and A/B test prompts using immutable commit hashes, ensuring stable, reproducible LLM deployments.

This comprehensive workflow pulls detailed analytics and audience insights from your Linktree profile. It measures key metrics such as total views, clicks, and conversion rates, while also providing deep dives into link performance ranking, top audience locations, referring sources, and device usage. Use this tool to understand your audience behavior and optimize your social media strategy.

This skill transforms an LLM into a disciplined wiki maintainer for Obsidian. It moves beyond simple RAG by incrementally ingesting sources (papers, notes, articles) to build a persistent, interlinked "Second Brain." The LLM manages cross-references, updates core concepts, and maintains an evolving knowledge graph, ensuring that knowledge compounds over time rather than being re-derived on every query. Ideal for deep research, personal knowledge management (PKM), and building comprehensive internal wikis.

This comprehensive checklist ensures that your Lucidchart integration is robust and resilient for production use. It covers critical areas such as OAuth2 token lifecycle management, handling document-level collaboration locks, managing rate limits, and ensuring correct API version pinning. By following these steps, developers can mitigate risks associated with concurrent edits, large diagram exports, and schema drift, guaranteeing a stable user experience.

Designs a scalable, version-controlled integration layer for the Lucidchart platform. This architecture tracks every shape mutation for diffing and rollback, implements real-time collaboration event consumption, and manages asynchronous export pipelines (PNG/SVG/PDF) using dedicated worker pools and caching strategies. Ideal for developing robust SaaS integrations requiring rigorous data synchronization.