Skill UI

A comprehensive toolkit for managing the entire lifecycle of feature flags, treating them as a controlled process rather than simple if-statements. This system provides scripts to scan for technical flag debt, plan progressive rollouts (e.g., ring, linear), and audit for crucial kill-switches. Ideal for release engineering, ensuring features are properly launched, tested, and safely retired.

This tool automatically converts design screenshots or visual exports into structured, functional Vue 3 Composition API components. It supports popular UI libraries like Vant, Element Plus, and Ant Design Vue. By batch converting screenshots, it streamlines the development process from raw design assets to reusable, production-ready code, significantly boosting frontend development efficiency.

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.

This skill is designed for orchestrating complex, multi-step processes. It helps manage workflows, coordinate different components, and ensure systematic execution of tasks from planning to completion. Ideal for complex automation scenarios and structured project management.

A powerful solution for handling background jobs and asynchronous tasks within Django applications using Celery. It facilitates task queuing, reliable worker management, scheduled execution (cron jobs), and robust error handling. Ideal for sending emails, processing heavy data loads, or managing complex, multi-step workflows without blocking the main thread.

This tool generates comprehensive API documentation directly from source code. It supports various API types, including REST, GraphQL, and RPC, and extracts crucial details like endpoints, parameters, data models, and authentication methods. It outputs standard formats such as Markdown, OpenAPI 3.0 YAML, and API Blueprint, streamlining the process of creating accurate and complete interface specifications for development teams.

This tool simulates a rigorous, relentless interview process designed to stress-test any plan, design, or architectural concept. It forces the user to walk through every decision branch, resolving dependencies one by one until a comprehensive, shared understanding is achieved. Ideal for developers and product managers needing to validate complex system designs or roadmaps.

Simulates a comprehensive, multi-stage academic journal peer review process. This agent dynamically configures five expert reviewers (EIC, 3 peers, and a Devil's Advocate) to evaluate a paper across methodology, domain expertise, cross-disciplinary impact, and core arguments. It provides structured reports, editorial decisions, and revision roadmaps, supporting full reviews, post-revision verification, and calibration modes.

This tool outlines the complete end-to-end migration process from an Oracle database environment to SQL Server. It automates schema conversion, data migration, and generates necessary assessment reports by simulating SSMA console operations. Ideal for database architects and developers planning heterogeneous database migrations.

Generates a highly polished, self-contained single-page HTML landing page optimized for maximum conversion. It incorporates advanced features like 3D CSS animations, GSAP scroll effects, and mouse parallax depth. To ensure accuracy, the skill uses a structured intake process (product pitch, target audience, brand colors, and tone) to build a conversion-ready page that reflects the actual product, not generic boilerplate. Outputs a single, deployable HTML file.

A comprehensive skill for capturing and documenting web application and graphical UI states during the development cycle. It supports full-page captures using Playwright, reliable post-processing cropping with PIL, capturing interactive states (hovers, selections), and even handles non-web desktop applications using mss/ctypes.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).