Skill UI

Transforms the AI into a highly personalized virtual tutor, adopting a defined persona, teaching style, and emotional relationship. This skill uses the Socratic method and advanced psychological principles (like Self-Determination Theory and memory scaffolding) to guide users through discovery learning. It doesn't just deliver answers; it fosters genuine engagement, maintains continuity across sessions, and motivates the user to learn by simulating the experience of a caring, challenging human mentor.

This guide provides a comprehensive framework for debugging and analyzing AgentCore runtime sessions using CloudWatch Logs Insights. It details advanced techniques like OpenTelemetry (OTEL) span correlation, resolving session IDs to trace IDs, and structuring complex query queries. Use this when investigating agent execution flows, diagnosing tool call failures, analyzing latency, or building detailed behavioral timelines.

This guide provides production-ready patterns for integrating with Bright Data proxy services. It covers critical aspects like setting up a proxy client, implementing robust retry logic for transient errors (e.g., 502, 503), managing sticky sessions for consistent IPs, and parsing complex HTML responses. Essential for building reliable, high-scale web scrapers using TypeScript and Python.

A persistent memory kit designed for Claude AI agents. It maintains deep context across multiple sessions and projects using a two-layer architecture (hot cache and knowledge wiki). Features include safety hooks, multi-project context isolation, and a /close-day command for daily synthesis, ensuring agents remember complex information and continuously learn.

A comprehensive guide to implementing production-ready patterns for interacting with the Klaviyo API via the Node.js SDK. This includes best practices for handling singleton sessions, creating type-safe API wrappers, implementing robust retry logic for rate limits, managing cursor-based pagination, and supporting multi-tenant environments. This ensures reliable and maintainable Klaviyo integrations.

This skill provides comprehensive guidance on correctly configuring Model Context Protocol (MCP) servers within Claude Code. It details the critical concepts of configuration scope (user vs. project) and outlines best practices to prevent context pollution across different coding sessions. Users learn how to safely add, remove, and clean up MCP settings using specific JSON files, ensuring a stable and efficient development environment.

A tool designed for persistent context management within AI coding sessions. Memory Kit solves the problem of context loss that occurs during compaction or session restarts by saving, loading, updating, and sharing critical session state to a dedicated `MEMORY.md` file. Key functions include creating snapshots of goals and decisions, syncing context across team members via Git, and auditing/pruning stale entries, ensuring continuous workflow and knowledge retention.

This guide provides essential knowledge for handling common errors encountered when integrating with Veeva Vault. It covers REST API usage, VQL querying patterns, and VAPIL Java SDK concepts, helping developers manage document lifecycles and resolve issues like invalid sessions, insufficient permissions, or data validation conflicts in a life sciences CRM environment.

This bundle provides comprehensive debugging guidance for Veeva Vault, covering REST API interactions, advanced VQL querying, and utilizing the VAPIL Java SDK. It helps developers manage document lifecycles, authenticate sessions, and resolve common operational and data access errors within the life sciences domain.

A comprehensive guide for simulating a full Software Development Life Cycle (SDLC) using specialized AI roles. It defines protocols for managing cross-functional teams (Dev, QA, DevOps, Product), covering sprint planning, codebase management, bug tracking, and deployment, ensuring context survival across multiple chat sessions.

Cavecrew provides a set of specialized subagents (investigator, builder, reviewer) designed for efficient code development delegation. Unlike vanilla agents, Cavecrew compresses output results, drastically reducing the token usage injected back into the main context. This allows users to maintain context over much longer, complex coding sessions, effectively preventing context exhaustion during large-scale refactoring, debugging, or multi-step feature development.