Skill UI

This skill helps users create a new Git branch that strictly adheres to established project naming conventions (e.g., Sentry standards). It automatically determines the appropriate branch type (such as `feat`, `fix`, `chore`, etc.) and generates a descriptive, standardized branch name by analyzing the provided work description or local code differences (diff). It guides the entire branching workflow, ensuring proper lineage and classification for code submissions.

This skill assists developers in understanding, writing, and validating EAS workflow YAML files for Expo projects. It provides comprehensive guidance on CI/CD pipelines, job definitions, triggers, and expression syntax, ensuring configurations are accurate and up-to-date by referencing official Expo schemas. Use this when automating builds or deployments via EAS.

This guide outlines a systematic process for transforming any recurring technical pattern, complex debugging solution, or workflow into a standalone, portable skill. It details the multi-step extraction workflow, including pattern identification, structured documentation generation (SKILL.md), and quality control checks to ensure the skill can be reused across different projects.

This skill outlines a comprehensive methodology for designing, building, and deploying robust LLM-powered applications. It covers assessing task-model fit, designing modular pipelines (acquire -> prepare -> process -> parse -> render), and managing state using file systems to ensure scalability and reliability in AI systems.

This skill provides a robust and safe mechanism for updating SpecKit templates and configurations from GitHub. It is designed to automatically apply the latest changes while meticulously preserving any existing project customizations, ensuring a non-disruptive workflow. It features a conversational, two-step approval process, guiding the user through the update process, reporting conflicts, and handling fresh installations gracefully. Ideal for developers needing reliable, version-controlled updates to their SpecKit environment.

A powerful code review utility designed for SwiftUI projects. It comprehensively analyzes code quality, ensuring adherence to modern Swift APIs, optimal performance, robust data flow management, and compliance with Apple's Human Interface Guidelines and accessibility standards (like VoiceOver and Dynamic Type). Use this tool when writing, refactoring, or reviewing complex SwiftUI implementations to maintain high code hygiene and maintainability.

Automates project-aware diary maintenance by recording status from conversations, refreshing context, extracting global and project progress, and syncing to Notion/Obsidian while enforcing strict workflow steps.

A comprehensive domain orchestrator designed to manage the entire project delivery lifecycle. It can route specific project management inquiries (e.g., Jira permissions, sprint velocity) to specialized sub-skills, or execute complex, goal-oriented workflows through a gated agentic loop. This process pulls live data from Jira/Atlassian, runs deterministic analytics, and verifies every step to ensure auditability and successful closure.

A comprehensive guide to implementing Clean Architecture patterns for both Android and Kotlin Multiplatform (KMP) projects. It covers robust module structuring, dependency inversion rules, defining UseCases and Repositories, and designing the data layer using technologies like Room, SQLDelight, and Ktor. Learn how to separate concerns, maintain platform independence, and manage complex data flows.

A comprehensive guide to mastering structured concurrency, reactive streams, and state management in Kotlin. Covers advanced topics like Flow operators (debounce, retryWhen), StateFlow for UI state, and implementing robust asynchronous logic for Android and Kotlin Multiplatform projects. Essential for modern Android development.

A forensic tool for performing post-mortem analysis on AI-assisted coding sessions. It goes beyond simply stating what was done, determining *why* work deviated (e.g., spec ambiguity, repo friction, agent error), identifying scope creep, and classifying rework patterns. It provides evidence-backed recommendations to improve prompts, codebase health, and future development workflows.

This advanced workflow orchestrates the entire research idea lifecycle. Starting from a broad research direction, it systematically executes literature mapping, creative brainstorming, novelty verification, and proposal refinement. The final output is a validated IDEA_REPORT, a detailed proposal, and a concrete experiment plan, transforming preliminary concepts into actionable, structured research projects. Ideal for users needing a full, end-to-end research guidance system.