Skill UI

This model provides an engineering operational framework for teams that leverage AI agents to generate large volumes of code. It shifts the focus from simple syntax to process quality, robust architecture design, rigorous testing, and systematic risk control, ensuring the development of highly stable and reliable systems in AI-assisted environments.

This comprehensive guide covers best practices for building modern Angular applications. It provides detailed instructions on component architecture, state management using Signals, advanced routing, dependency injection, handling forms (prioritizing Signal Forms), and implementing accessibility (ARIA). It also details setup procedures for new projects and modern rendering strategies like SSR.

This guide outlines how to build new API connectors or providers that strictly adhere to the existing integration architecture and patterns of a target repository. It is designed for adding integrations while maintaining architectural consistency (e.g., layout, configuration schema, authentication model, and testing style), preventing the creation of novel, unsupported patterns.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.

This skill provides a rigorous, structured method for inspecting animated 3D characters, rigs, and motion retargeting in Blender. It moves beyond visual evidence (screenshots) by extracting and comparing structured data points such as bone transformations, bounding box changes, ground contacts, and axis conventions. Ideal for diagnosing subtle animation flaws like foot sliding, ground penetration, or incorrect orientation that are invisible in still images.

This skill provides comprehensive web browser automation capabilities for agents. It utilizes AI-optimized snapshots, reducing context size by 93% by using element references instead of full DOM. Functions include navigation, interactive element extraction, form filling, data scraping, and state management across multiple isolated sessions. Ideal for complex web testing and data extraction workflows.

This tool enables web interaction using natural language descriptions instead of complex CSS selectors. By utilizing a specialized page-agent and an LLM-driven tool-call loop, users can simply state their goal (e.g., "Fill the search box with cats and submit"). It is ideal for dynamic web pages, ambiguous structures, or quick, one-shot interactions where robust selector writing is impractical. The system provides graceful degradation if the advanced page-agent is unavailable.

Compares two recorded browser sessions step-by-step using matching step IDs. This tool performs both pixel-level visual regression analysis (calculating MSE/PSNR) and comprehensive DOM comparison using accessibility snapshots. It provides a detailed divergence report, making it crucial for validating UI changes, detecting visual regressions after updates, and ensuring that browser replay runs match the parent session within defined tolerances.

Bun is a high-performance, all-in-one JavaScript runtime and toolchain. It functions as a runtime, package manager, bundler, and test runner, offering significant speed improvements over traditional Node.js setups. It is ideal for modern, fast-paced development, new projects, and deployment environments like Vercel.

This tool serves as a persistent memory and state manager for complex coding projects within the Claude environment. It allows users to initialize new projects with structured metadata, track detailed session progress (including summaries, decisions, and next steps), and save the entire context reliably. By ensuring project continuity across disconnected sessions, it drastically improves the flow and consistency of the development workflow.

Generates structured CodeTour `.tour` files in JSON format for detailed, step-by-step code walkthroughs. This tool is essential for onboarding new engineers, conducting architectural reviews, or documenting complex PR changes. It provides a guided narrative that directs users to specific files and line anchors, ensuring a structured and focused learning journey.

Code Health MCP provides structural maintainability feedback and design-level health scores, going beyond standard linting. It is crucial for AI-assisted coding workflows, allowing users to review code quality, verify score deltas after changes, and gate commits or pull requests to prevent codebase regression. Use it when refactoring, updating legacy modules, or ensuring the integrity of large diffs.