Skill UI

Automate Worksnaps processes through Composio’s Rube MCP by discovering current tool schemas, managing toolkit connections, and executing compliant workflows with memory-aware multi-tool calls.

Orchestrates Yelp workflows via Rube MCP and Composio by walking through tool discovery, connection validation, schema-compliant execution, memory/session practices, and pagination-aware multi-tool calls.

Automates Zoominfo operations through Composio Rube MCP, guiding discovery, connection checks, and execution patterns with mandatory searches before every tool use.

Guides orchestrating Zyte API actions through the Composio Zyte API toolkit via Rube MCP; emphasizes searching tools first, establishing an active connection, and executing schema-compliant workflows with dedicated session and memory handling.

Detects system CPU, GPU, memory, and disk availability before heavy scientific tasks, writing `.claude_resources.json` with strategic recommendations (parallelism, out-of-core, GPU acceleration) so analysts choose appropriate compute approaches.

Polars is a blazing fast in-memory DataFrame library based on Apache Arrow that replaces pandas for 1-100GB workloads, offering expression-based lazy execution, parallel operators, and rich I/O for ETL pipelines.

Hierarchical Agent Memory (HAM) scopes Claude Code agent context by generating per-directory CLAUDE.md files, tracking token savings, and surfacing analytics via a dashboard so multi-folder projects avoid repeated full scans.

This comprehensive profiler provides systematic performance analysis for modern applications built with Node.js, Python, and Go. It detects critical bottlenecks across CPU, memory, and I/O dimensions. Key features include generating flamegraphs, analyzing bundle sizes, optimizing database queries (N+1 detection), and running rigorous load tests using k6 and Artillery. It mandates before-and-after measurements to ensure verifiable performance improvements.

A comprehensive expert for deploying and scaling AI agents using AWS Bedrock AgentCore. This guide covers the full lifecycle of agent management, including service selection (Gateway, Runtime, Memory, Identity, etc.), deployment patterns, credential management, and advanced integration workflows required for enterprise-scale AI solutions.

This advanced engine acts as the memory layer for C-suite advisory sessions. It loads, manages, and enriches detailed company context from local files, automatically detecting context staleness. Crucially, it enforces strict anonymization protocols before any external API calls, ensuring sensitive data (like revenue or names) is protected while providing deep, specific insights for high-level business strategy.

This comprehensive guide provides advanced troubleshooting workflows for complex, microservices-based environments running on Kubernetes. It covers diagnosing issues like CrashLoopBackOff, cascade failures, resource pressure (CPU/Memory), and detailed Redis state analysis, ensuring systematic root cause identification across multiple services.

A two-layer memory architecture designed for managing corporate board meeting decisions. It separates raw, unfiltered transcripts (Layer 1) from founder-approved, canonical decisions and action items (Layer 2). This system ensures historical accuracy, tracks overdue tasks via commands like /cs:review, and actively detects topic contradictions and conflicts to maintain governance integrity.