Skill UI

This guide assists developers in creating a systematic QA plan for RevenueCat integration. It provides a structured approach to verifying the entire subscription lifecycle, including initial purchases, renewal, upgrades, and cancellations. The core principle is linking tests to specific, verifiable dashboard signals, ensuring robust and reliable in-app monetization setups.

This utility is designed to reconcile the ADR (Architecture Decision Record) index when source files have been deleted or modified, preventing the accumulation of stale or dangling reference rows. Unlike simple upserts, this tool performs a hard purge of the entire index namespace (adr-patterns and adr-edges) and then fully rebuilds the index from the files currently present on disk. It is crucial for maintaining data integrity after deletions.

This skill guides users through a comprehensive, structured design process. It helps transform vague ideas or initial concepts into detailed, validated specifications by exploring project context, proposing multiple options with trade-offs, and iteratively refining architectural details. It is essential for defining clear boundaries and requirements before any code is written, ensuring a robust and well-documented development roadmap.

A powerful skill leveraging OpenAI Codex/GPT for autonomous, hands-off code generation, implementation, and complex task execution. It operates in sandboxed modes (Read-Only, Workspace-Write) to allow developers to refactor, fix bugs, and build features with minimal user intervention. Ideal for complex programming tasks, code reviews, and structured workflow automation.

This skill provides a comprehensive, end-to-end workflow for addressing GitHub issues. It guides the user through crucial development stages: understanding the issue, researching prior art in the codebase, planning the fix, implementing changes in small commits, rigorous testing (including unit and regression tests), and finally, submitting a structured Pull Request (PR) using the GitHub CLI. Ideal for any developer maintaining codebases.

Executes a multi-agent, structured code review workflow for GitHub Pull Requests (PRs). It analyzes changes from multiple perspectives (e.g., bug scans, compliance with project guidance, git history, etc.), provides confidence scoring, and generates actionable, highly formatted feedback directly on the PR. Use this when a thorough, professional code review is required.

This skill performs a comprehensive, setup-wide health check for agentic developers. It audits various components—including skills, memory, tools, configuration, and workflow habits—to identify inefficiencies and potential improvements. It provides a detailed report and guides the user through applying targeted fixes, ensuring the agent environment remains lean and optimized.

This comprehensive guide outlines an opinionated set of conventions for building robust Ruby on Rails applications. It covers core architectural principles, including rich models, state-as-records, minimal dependencies, and best practices for CRUD operations and testing. It is mandatory to consult these guidelines whenever designing, writing, reviewing, or refactoring any Rails code.

This skill acts as an advanced orchestration protocol for reviewing GitHub pull requests. It is stack-agnostic, meaning it does not enforce its own rules. Instead, it dynamically discovers the project's existing standards—such as the test runner, architectural conventions, and requirement specifications—before running six specialized subagents in parallel. It provides a comprehensive, context-aware review and summary directly on GitHub.

This skill summarizes user-provided input into one concise paragraph. It is specifically designed to enhance E2E (End-to-End) coverage testing within development environments, such as Agent Builders. The generated summary ensures comprehensive content representation and must include the E2E_SUMMARY_SKILL_PASS marker for validation.

A comprehensive guide for bringing RuView CSI sensing nodes (ESP32-S3/C6) online. This skill covers the full lifecycle: building the embedded firmware, flashing the device, provisioning WiFi credentials, and confirming the Continuous Sensing Image (CSI) data stream. Essential for physical hardware deployment and debugging of complex sensing systems.

This guide provides a comprehensive onboarding process for RuView (WiFi-DensePose). It details three deployment tiers: Docker simulation for quick testing and UI exploration, source code build verification (Rust/Python), and live sensing setup utilizing ESP32 hardware. Ideal for new users or rapid prototyping.