Skill UI

This guide provides a comprehensive quickstart for integrating with OpenRouter, a unified endpoint for accessing multiple large language models (LLMs). It includes examples in cURL, Python, and TypeScript, demonstrating how to send chat completion requests, handle complex JSON responses, manage model parameters, and calculate usage cost across various providers (e.g., Llama, GPT-4o, Claude). Ideal for developers testing API connectivity or building multi-model applications.

A specialized downstream skill for analyzing security vulnerabilities in complex agentic systems. This tool is designed for red teaming and penetration testing, focusing on detecting prompt injection, retrieval poisoning, memory contamination, planner drift, and tool boundary abuse within multi-step LLM chains. Use when proving how untrusted inputs compromise system integrity.

Enables agents to perform authorized security assessments, blue team exercises, and penetration testing on AI products, agents, and infrastructure. Uses first-principles reasoning to identify vulnerabilities like prompt injection and tool abuse, generating evidence-based security reports without relying solely on payload libraries.

Monitor and evaluate Retrieval-Augmented Generation (RAG) systems using measurable metrics. This skill covers retrieval quality checks like Recall@k, hallucination detection, and groundedness scoring. It enables continuous regression testing and production monitoring for AI pipelines using Python libraries like RAGAS and OpenTelemetry.

A comprehensive asset discovery pipeline for authorized security assessments. It automates subdomain enumeration, live host detection, URL crawling, and vulnerability scanning using tools like subfinder, httpx, nuclei, and katana, delivering prioritized URL lists for penetration testing.