Skill UI

Automatically collects comprehensive diagnostic evidence for Mistral AI support tickets. This bundle includes environment details (OS, Node/Python versions), installed SDK versions, API connectivity test results, available models, and recent error logs. It is essential for reproducing and diagnosing persistent issues when contacting technical support.

A comprehensive workflow designed for clinical professionals to search, retrieve, and synthesize medical evidence. It allows users to query clinical literature with specialized filters (e.g., specialty, evidence level), check potential drug interactions against patient profiles, and look up the latest specialty guidelines from major health organizations (like ACC/AHA, NICE). The output provides structured citations, confidence scores, and evidence grading to support informed clinical decision-making.

This guide provides comprehensive steps to install and authenticate the OpenEvidence SDK/API. It covers setting up environment variables, installing required packages (supporting both Node.js and Python), and verifying the connection using sample code. This is essential for developers integrating OpenEvidence's medical AI capabilities for clinical decision support and evidence-based queries into a new application.

Assess research claims and experimental rigor by evaluating methodology, statistical validity, evidence quality, and biases using GRADE and Cochrane ROB frameworks, plus supporting schematics for complex concepts.

Leverages firecrawl and exa MCP tools to run focused multi-source searches, scrape key documents, and synthesize citation-backed reports whenever a user needs thorough evidence-based research on any topic.

This workflow manages the complex process of responding to external academic reviews (e.g., ICML, OpenReview). It parses raw reviews, atomizes concerns into an issue board, and drafts safe, text-only rebuttals. The system enforces strict grounding (Provenance Gate) and commitment checks to ensure all claims are supported by the paper, reviews, or user-confirmed evidence, making it ideal for post-submission refinement.

Assess research claims and experimental rigor by evaluating methodology, statistical validity, evidence quality, and biases using GRADE and Cochrane ROB frameworks, plus supporting schematics for complex concepts.

This tool collects comprehensive diagnostic evidence for troubleshooting Anthropic Claude API issues. It gathers critical data such as request IDs, rate limit headers, SDK versions, and connection details. It is essential for generating accurate support tickets or diagnosing persistent API failures.

This bundle collects comprehensive diagnostic evidence for ElevenLabs services. It automatically gathers SDK versions, API connectivity status, quota usage, voice inventories, and available model metadata. Use this tool when encountering persistent bugs or preparing comprehensive support tickets for technical support.