Skill UI

An expert system for designing and implementing advanced AI context architectures. It specializes in integrating intelligent memory systems, vector databases, and knowledge graphs to ensure AI applications maintain coherent, relevant, and scalable state across complex, multi-agent workflows. Essential for enterprise RAG implementation and stateful AI development.

This skill details advanced techniques for enhancing the effective context capacity of LLMs. It outlines four core strategies—Compaction, Observation Masking, KV-Cache Optimization, and Context Partitioning—to prevent context limits from constraining task complexity. By strategically managing token usage, users can reduce operational costs, minimize latency, and implement robust, long-running agent systems for handling large documents or conversations.

This skill set provides advanced, structured strategies for optimizing Large Language Model (LLM) interactions. It covers techniques such as intelligent context summarization, dynamic trimming, context routing, and precise token budget allocation to prevent 'context rot'. It is essential for building robust, long-running, multi-turn conversational AI systems.

This skill automatically fetches the latest official documentation for programming libraries and frameworks (such as React, Next.js, or Prisma) via the Context7 API. It is essential for developers who require accurate, up-to-date technical reference material to ensure their code adheres to the most current best practices.

Automatically evaluates Claude Code sessions at the Stop hook, identifies reusable patterns, and stores them as learned skills for future reuse, helping you capture troubleshooting steps, debugging techniques, and project conventions without manual effort.

This advanced system transforms session interactions into reusable, atomic knowledge units called "Instincts." By hooking into tool usage and session activity, it observes patterns (like preferred coding styles, error fixes, or repeated workflows). These instincts are then clustered and "evolved" into structured Skills, Commands, or specialized Agents, capturing deep contextual knowledge with weighted confidence scoring to enhance development productivity.

Contract Test Creator automatically assists with designing and implementing contract tests, guiding on best practices, producing production-ready code and configurations, and validating results whenever the user invokes contract test creator tasks.

Automates contributing guide creation in technical documentation; triggers on explicit requests, follows best practices, offers step-by-step help, generates code/config samples, and validates outputs for API docs, user guides, and architecture docs.

Orchestrates Control D operations via Composio’s Rube MCP, requiring tool discovery, active connections, and schema-compliant calls before executing workflows.

Persistent LLM conversation memory that manages short-term, long-term, and entity-focused layers to store, retrieve, and consolidate memorable context for smarter conversational AI agents.

Automates Conversion Tools workflows by orchestrating Composio’s toolkit through Rube MCP, guiding users to discover current schemas, verify connections, and execute schema-compliant tool calls with memory/session handling.

Guides using Rube MCP via Composio to discover Convertapi tool schemas, manage toolkit connections, and execute safe multi-step conversions without hardcoded slugs.