Skill UI

This example demonstrates the structure of a blocked fixture within a testing framework. It serves as a placeholder to illustrate required missing elements, such as a detailed description, and is useful for understanding fixture setup requirements and testing methodology.

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 skill is designed to review Chinese skill documentation to ensure it meets publishing standards. It systematically checks the clarity of descriptions and the executability of process steps, providing structured feedback in Chinese while maintaining necessary machine enumeration values for technical integrity.

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 transforms unstructured task lists into a disciplined, protected daily schedule. It implements the Deep Work methodology by classifying tasks into deep and shallow categories, budgeting shallow work time, and creating an energy-first time-blocked plan. It enforces strict limits, such as a 4-hour deep work ceiling, ensuring focus remains the protected resource throughout the day. Includes logging and end-of-day shutdown rituals.

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.

A comprehensive, human-guided onboarding skill designed for users new to AI coding agents and Power BI agentic development. It provides structured setup help, deep conceptual explanations, and conversational guidance, mimicking a mentor's session. Modes include concise setup assistance and deep conceptual learning. Use cases: Setting up a new agent environment, understanding core AI concepts (models, prompts, tools), or auditing existing agent configurations.

This skill enforces rigorous meeting discipline through a four-stage workflow: Cost Gating, Timeboxed Agenda Building, Running the Meeting, and Action Item Extraction. It calculates meeting costs, ensures every agenda topic has a desired outcome, and converts raw notes into a structured, owner-assigned, due-dated checklist, flagging any missing owners or deadlines. Ideal for transforming unproductive meetings into actionable, accountable outcomes.

This guide outlines the essential CLI commands for managing the full task lifecycle within the LobeHub task system. It covers viewing task details, creating and managing subtasks with dependencies, handling task-related documents (workspace), and tracking conversational topics. Use `lh task` to ensure structured workflow execution and progress reporting.

This skilled searches GitHub Issues and Discussions to find prior reports, error matches, and compatibility clues for software debugging. It extracts details on exact errors, package versions, OS environments, and recommended workarounds. Use this workflow for diagnosis and discovery, not for academic citation. It guides structured queries to provide actionable debugging steps and compatibility summaries.