Skill UI

This guide provides a comprehensive roadmap for migrating and upgrading integrations with the OpenEvidence clinical AI platform. It addresses critical API changes, such as schema restructuring (e.g., flat answers to structured evidence), version detection, and updated citation formats. Developers can use this knowledge to implement robust migration logic, ensuring that downstream clinical applications maintain high levels of accuracy and safety when accessing evolving medical evidence.

This skill provides comprehensive tools to monitor the real-time availability, status, and performance of various large language models (LLMs) accessed via OpenRouter. It supports active health probes, catalog checks, and scheduled monitoring via Python and Bash, ensuring robust fault detection and failover logic for production systems that rely on external AI APIs.

Enables Claude to invoke the computer-vision-processor plugin, auto-generating Python calls to run object detection, classification, and segmentation on user-provided images for detailed analysis.

This comprehensive guide details how to configure robust multi-environment deployments (Development, Staging, Production) within the Replit ecosystem. It covers best practices for database separation, managing environment-specific secrets, implementing reliable environment detection logic, and setting up CI/CD pipelines to ensure applications are stable and secure across all deployment stages.

Secret Scanner Assistant auto-activates within Security Fundamentals to guide you on secret detection, authentication, validation, secure coding, and vulnerability checks with best practices.

Automates the creation and validation of security headers by guiding users through authentication, input validation, secure coding, and vulnerability detection practices within the Security Fundamentals domain.

Runs Semgrep static analysis with auto language detection, parallel Task subagents, Semgrep Pro checks, and configurable “run all” or “important only” modes to audit codebases for vulnerabilities and bug patterns.

Comprehensive skill set covering the full lifecycle of advanced visual AI systems. Expertise includes object detection (YOLO, Faster R-CNN), instance and semantic segmentation (Mask R-CNN, SAM), model training using PyTorch, and production deployment optimization using ONNX and TensorRT for edge or cloud targets.

A comprehensive toolkit for the full software development lifecycle. It guides stack selection using a detailed decision engine, automatically scaffolds complex boilerplate projects across multiple popular stacks (Next.js, MERN, FastAPI, Django), and provides deep code quality analysis. Features include security vulnerability detection, complexity scoring, and dependency auditing, ensuring high-quality development from the start.

Session Security Guide supplies automated, production-ready assistance for session security checker tasks, offering best practice guidance on authentication, validation, secure coding, and vulnerability detection.

This skill guides the detection of unintended visual changes in user interface (UI) components. It works by capturing screenshots and performing pixel-by-pixel comparisons against approved baselines. It is essential for ensuring UI consistency across code changes, responsive breakpoints, and differing environments. Supports modern tools like Playwright, Percy, and BackstopJS.

Assesses AI/ML models and datasets for ethical risks, fairness concerns, and bias, generating reports and mitigation guidance via the ai-ethics-validator plugin whenever a user requests an ethics review or bias detection.