Skill UI

This skill generates comprehensive, tailored instruction files for AI coding assistants like GitHub Copilot and Claude. It supports multiple strategies (flat or nested) and is specifically designed for managing complex monorepos by creating area-scoped instructions using `applyTo` globs. Use it to standardize AI tooling usage across large codebases.

Manage and apply custom policies to customize readiness scoring across development artifacts. Users can set pass-rate thresholds, override criteria impact, or disable irrelevant checks to tailor scoring to specific organizational standards or project needs. Essential for CI gating and ensuring compliance.

The Desktop Commander MCP grants agents deep reach across the user's entire operating environment, extending far beyond the typical IDE sandbox. Key capabilities include maintaining persistent shell sessions, managing long-running background processes, accessing arbitrary filesystems, and natively handling structured data formats (Excel, PDF, DOCX). It also enables remote operations via SSH and large-scale content search, making it ideal for complex, multi-turn development, DevOps, and data analysis workflows.

An expert playbook detailing advanced techniques for pivoting across compromised Linux hosts. Techniques cover SSH agent hijacking, credential harvesting from common system files, key extraction, and abusing internal services via D-Bus and systemd exploitation, crucial for post-exploitation stages.

This tool searches a comprehensive database of over 2500 curated open-source repositories for tools related to Large Language Models (LLMs), ChatGPT, RAG, agents, and NLP. It interprets natural language queries, converts non-English inputs to core English keywords, and systematically filters results across multiple specialized categories (e.g., LangChain, Chatbots, CLIs). Use it whenever the user needs to find specific AI development libraries or open-source AI tooling.

A powerful skill that enables natural-language interaction with complex DeFi protocols across multiple EVM chains. It acts as a non-custodial agent, interpreting user prompts (e.g., 'swap X for Y') into simulated, multi-step transactions (like approve + swap). It utilizes account abstraction (EIP-7702/ERC-4337) to simulate and queue secure, user-signed transactions via the CLI, making advanced DeFi accessible from the terminal.

This skill guides the design and optimization of production-grade multi-agent systems. It specializes in using LangGraph, LangChain, and DeepAgents to create structured, complex AI workflows. It covers state management, agent routing, memory integration, and tool calling, making it ideal for building robust, scalable agents like supervisors, planners, and coders.

This CLI alias serves as a system maintenance tool for PUA agent state. It scans for stale PUA agent data, identifying and safely removing only confirmed orphan records to maintain system integrity. It also manages configuration files, ensuring unknown fields are preserved when updating the primary config JSON.

A comprehensive skill for integrating X (Twitter) data into applications, scripts, data pipelines, and AI agents. It supports advanced scraping tasks including tweet searching, user lookup, following export, and media downloading. Functionality is exposed via generated SDKs (Python, TypeScript, Go, etc.), REST endpoints, signed webhooks, and the MCP server for agent automation.

Diagnoses full-stack failure modes in agent and LLM applications, including wrapper regressions, memory contamination, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings and code-first fixes for production agent systems.

Use this skill to deeply inspect and audit the entire process of local AI coding-agent sessions. It tracks critical operational metrics such as token consumption, cost spikes, tool failures, latency anomalies, and overall health scores. Ideal for debugging unreliable code runs, establishing CI/CD health gates, or comparing different attempts to ensure semantic accuracy.

Expert skill for building Model Context Protocol (MCP) servers and tools from scratch. Covers the full development lifecycle—from defining tool schemas and resources to implementation, testing, and publishing to registries. Supports robust patterns using TypeScript and Python for integrating custom capabilities into AI agents.