Skill UI

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.

This guide addresses critical LangGraph streaming pitfalls, including state overdraw, proxy buffering issues (Nginx, Cloud Run), and excessive event noise. It provides a production-grade pattern for implementing robust SSE/WebSocket endpoints using FastAPI. Learn how to correctly select the `stream_mode` (messages, updates, values) and implement server-side event filtering to reliably build live-token chat UIs and perform comprehensive state visualization.

Master advanced patterns for composing LangGraph subgraphs, which is essential for building robust, multi-agent systems like planner-executors or hierarchical teams. This skill addresses critical issues such as shared state contract propagation (P21) and callback scoping (P28). Learn to manage state across independent graph components using sophisticated dispatch patterns: compiled nodes, Send fan-out, and Command bubble-up.

This skill guides the systematic process of conducting comprehensive academic literature reviews. It allows users to search multiple biomedical, scientific, and technical databases (e.g., PubMed, arXiv, Semantic Scholar) to synthesize current knowledge. The output generates professionally formatted reports (Markdown/PDF) with verified citations, and mandatorily integrates AI-generated scientific schematics to enhance visualization and depth, suitable for research papers, meta-analyses, and state-of-the-art reports.

This bundle collects comprehensive diagnostic evidence from the MindTickle sales enablement API. It gathers data on API token validation, course catalog status, user enrollment, assessment progress, and CRM sync state. It allows users to diagnose complex issues like content gaps, scoring discrepancies, and SSO failures without requiring admin access, providing a complete diagnostic tarball for support teams.

A comprehensive checklist for deploying Miro REST API v2 integrations into a production environment. This guide covers critical best practices including OAuth scope minimization, robust error handling, rate limit management, implementing circuit breakers, health checking, and defining clear rollback procedures. Use this when moving any Miro-integrated application to a live, customer-facing state.

A comprehensive guide providing production-ready, structured patterns for interacting with the Miro API. It covers best practices for both the high-level stateful client usage and the low-level REST API v2. Includes patterns for implementing robust Board Services (fetching, pagination) and Item Factories (creating various elements like sticky notes, shapes, and cards). Essential for developers building SaaS applications or complex automation workflows using Miro.

A comprehensive methodology and checklist for identifying and exploiting race conditions (TOCTOU) in web applications. It guides users to find timing windows, detect vulnerabilities like double-spend or rate limit bypass, and exploit concurrent request flaws in state-changing business logic. Essential for penetration testing and bug bounty hunting.

This skill provides a comprehensive guide to setting up robust CI/CD pipelines for Oracle Cloud Infrastructure (OCI). It leverages GitHub Actions and Terraform to automate the deployment, planning, and testing of OCI resources. Instructions cover secure API key authentication, best practices for managing Terraform state, and crucial workarounds for known OCI provider bugs, ensuring stable and reliable cloud deployments.