Skill UI

Explores Feishu/Lark native OpenAPI docs when existing lark-* skills or CLI commands lack coverage, fetching markdown indexes stepwise to surface raw API specs and ready-to-run `lark-cli api` invocations.

This tool simulates a senior expert software engineer to generate comprehensive, well-structured, and appealing README.md files for any project. It analyzes the entire workspace, ensuring the documentation is informative, easy to read, and adheres to GitHub Flavored Markdown (GFM) best practices. Ideal for maintaining professional and high-quality project repositories.

This skill automates the comprehensive localization and translation of an entire MkDocs documentation suite. It translates all Markdown files from source English folders into a specified target language, preserving the exact folder structure and Markdown formatting. Additionally, it updates include references and modifies the core mkdocs.yml configuration file to properly support the new locale, ensuring a seamless multilingual documentation setup.

Converts text-based documentation into structured Markdown by following explicit instructions, documented options, or reference files, supporting header levels, patterns, platforms, and cleanup steps for polished technical documents.

This tool acts as an expert technical documentation specialist, transforming lengthy, verbose official documentation from URLs into concise and actionable 'tldr' pages. It extracts the most common command patterns, adheres strictly to the tldr-pages markdown format, and provides clear, example-driven command references, making complex tools easy to reference.

Converts markdown documents to HTML via marked.js-style workflows, pandoc/gomarkdown knowledge, and templating systems like Jekyll or Hugo for both single-file and batch pipelines, enabling static site previews, documentation, and CLI/Node toolchains.

Transforms repo structure and commit history into two actionable markdowns—an architecture summary and a narrative story—so analysts can trace system intent, data flow, and team evolution.

Automates the creation of copy-paste ready implementation documentation by parsing a PR plan, extracting numbered steps, and emitting precise, executable markdown files with file paths, code blocks, and verification checklists for every action.

Automates updating a markdown document with an index/table listing files from a designated folder, handling discovery, structure selection, and syntax validation to keep documentation in sync.

Defines a Markdown/Mermaid-first documentation skill for scientific and technical writing, providing diagram standards, 24 reference types, and templates so every report, README, or analysis stays text-first, versionable, and visualization-ready.

MarkItDown converts PDFs, DOCX, PPTX, XLSX, HTML, JSON, XML, archives, YouTube links, images via OCR, and audio via transcription into clean Markdown, providing token-efficient text ready for LLMs and documentation workflows.

Execute comprehensive document workflows using Adobe PDF Services API. This skill allows you to convert content (HTML/DOCX) into PDFs, extract structured text and tables from existing PDFs using Sensei AI, generate dynamic documents from Word templates, and convert PDFs to Markdown. Ideal for building robust document automation pipelines and advanced content extraction solutions.