Skill UI

A sophisticated AI system that coordinates multiple specialized agents (e.g., Security Auditors, Performance Analysts, Architecture Specialists) to perform comprehensive, multi-perspective code assessments. It analyzes code context, manages state, and synthesizes conflicting insights to provide deep, holistic reviews for complex software projects.

This comprehensive guide walks developers through migrating complex LLM codebases from raw SDK calls (OpenAI, Anthropic) or legacy frameworks (LlamaIndex) to the structured LangChain framework. It covers code assessment, pattern-by-pattern migration, advanced agent construction, robust tool calling, and transforming custom RAG pipelines into scalable, standardized chains.

This comprehensive guide demonstrates how to build a robust AI language tutoring session using the Speak SDK. It covers initiating conversations, submitting student responses (text or audio), performing deep pronunciation assessment at the phoneme level, and generating detailed session summaries with grammar and vocabulary metrics. Ideal for developing language education platforms and testing API integration.

Interactive assessment that gauges whether your product work is AI-first or AI-shaped, measures readiness across five essential PM competencies for 2026, highlights gaps, and recommends which AI capability to build next.

A comprehensive guide to building production-grade evaluation systems for Large Language Models (LLMs). This skill covers advanced methodologies, including Direct Scoring and Pairwise Comparison, alongside critical techniques for mitigating systematic biases (e.g., Position Bias, Length Bias). Learn how to select appropriate metrics and structure prompts to ensure reliable, consistent, and objective quality assessment across various AI applications.

Analyze travel health risks for destinations, recommend vaccines and travel medicine, and generate multilingual emergency medical cards using WHO/CDC-style guidance. Useful for pre-trip planning, risk assessment, and post-travel monitoring.

This skill facilitates autonomous, multi-round research review and refinement. It continuously submits work for assessment via external reviewers (Codex or manual), implements suggested fixes, and re-reviews until the designated positive threshold is met or the maximum number of rounds is reached. It manages state persistence and adjusts difficulty levels for rigorous, iterative quality assurance.

This skill automates the research improvement process by creating a closed loop: Review -> Implement Fixes -> Re-review. It leverages any OpenAI-compatible LLM API to iteratively refine research work until a positive assessment is reached or a maximum round limit is hit. Ideal for academic or technical project refinement.

This advanced skill automates the rigorous, iterative review and refinement of complex research topics or papers. It runs multi-round cycles, using an external LLM (MiniMax API) to provide continuous, constructive feedback. The process guides the user through review, fixes, and re-review stages until a positive assessment is achieved or the maximum round limit is reached. It includes robust state persistence for long-running academic workflows.

This guide details comprehensive physical security penetration testing techniques, essential for red teaming engagements. It covers methods such as tailgating, badge cloning (RFID), lock bypassing, and deploying rogue network devices (e.g., Pineapple, LAN Turtle). It provides practical toolkits and MITRE ATT&CK mapping to evaluate an organization's physical and digital control weaknesses.

This skill systematically probes an AI model's core behavioral patterns across six critical dimensions, including reasoning, refusal, formatting, and grounding. It generates a comprehensive, styled HTML report with radar charts and actionable insights, allowing users to understand a model's true capabilities, compare different models, or perform compliance and red-team assessments without needing an external API key.

Assesses AI/ML systems for prompt injection, jailbreak, model inversion, data poisoning, and agent tool abuse using MITRE ATLAS mapping, signature detection, and scoring metrics before deployment.