Skill UI

Guides developers to wrap Feishu API calls into reusable lark-cli skills, covering API research, command templates, and best practices for authentication, permissions, and orchestration.

Guides agents through researching Microsoft technologies via Learn MCP docs, then scaffolds hybrid skills that store essential knowledge locally while enabling dynamic lookups for depth.

Helps teams discover, install, upload, and sync AI skills stored in a Nacos registry via the nacos-cli tool, guiding users through finding relevant skill names, configuring profiles, and running install commands.

Use the provided helper scripts to track and manage OpenCode sessions, list tasks, and inspect messaging status from the workspace; run them via `uv run python skills/opencode/<script>.py` with Python 3 available.

A comprehensive workflow for the full lifecycle management of AI skills. This tool guides users through creating skills from scratch, modifying existing ones, and rigorously benchmarking performance. It supports iterative refinement, quantitative evaluation, and optimizing skill descriptions for maximum triggering accuracy.

This meta-skill provides a comprehensive guide through the entire software development lifecycle (SDLC). It teaches senior-level engineering discipline, covering everything from vague idea refinement and specification design to planning, implementation, testing, code review, and deployment. It emphasizes core behaviors like surfacing assumptions, managing ambiguity, maintaining scope discipline, and enforcing technical simplicity.

A comprehensive workflow for discovering, integrating, and utilizing third-party APIs and SDKs. This skill guides the process by first detecting the project language, ensuring necessary guidelines and skills are present, systematically fetching API details, and providing structured guidance on authentication, model usage, and endpoint implementation. It tracks integration progress by recording specific development milestones (e.g., SDK setup, first call made).

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

This skill serves as the foundational plumbing layer, enabling AI agents to reliably connect with and interact with the Power Automate platform via the FlowStudio MCP server. It provides essential capabilities such as secure authentication setup, reusable helper functions (Python/Node.js), advanced tool discovery (`list_skills`, `tool_search`), and robust response handling, making it the required starting point for building complex automation workflows.

Guides teams through creating a complete GitHub Copilot configuration by outlining required instructions, reusable skills, and agent/workflow files tailored to the chosen tech stack and workflow preferences.

Use terminal commands to discover, list, create, edit, move, copy, enable/disable, and delete AI agent skills across 11 tools, handling format conversions and scope overrides between global and project configurations.

This skill serves as a comprehensive index for the built-in QA Agent, mapping user topics and keywords (such as installation, configuration, skills, or memory) directly to specific QwenPaw official documentation paths and relevant source code entry points. It drastically reduces the need for blind searching by providing a structured guide, ensuring the QA Agent reads the most accurate and relevant files first.