Skill UI

Keeps task_plan.md, findings.md and progress.md on disk as durable working memory for multi-step AI agent runs; lifecycle hooks inject project-scoped plan context, with local-only session recovery for research tasks needing 5+ tool calls.

Persist multi-step AI agent work using Markdown files on disk: task_plan.md, findings.md and progress.md. Lifecycle hooks inject project plan context, restore state across sessions, and keep long research or tasks with more than five tool calls on track.

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.

Reads and summarizes local text-based files such as Markdown, JSON, CSV, and source code, including quick type checks and smart tailing for big logs while skipping PDFs, images, and binaries.

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.

This skill automatically updates a markdown file with an index or table of files from a specified folder. It scans the target file, discovers files matching a pattern, and generates a structured list or detailed table. It supports simple lists, detailed tables, or categorized sections, preserving existing markdown formatting and using relative paths for links.

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

A comprehensive skill for creating technical and scientific documentation using Markdown as the source format, enhanced by embedded Mermaid diagrams. This method establishes text-based diagrams as the canonical standard, ensuring that all visualizations are clean, editable, and highly readable in version control systems like Git. It is ideal for generating reports, architectural diagrams, workflows, and any content that requires cross-platform rendering and version history.

Convert PDF, Office, HTML, CSV, EPUB and other documents into structure-preserving Markdown with Microsoft MarkItDown. Covers safe local and stream conversion, batch workflows, plugins, vision OCR, Azure extraction, and MCP integration for search and LLM/RAG ingestion.

A comprehensive guide and set of production-tested scripts for migrating notes between popular platforms like Apple Notes, Obsidian, and Notion. It addresses key technical challenges such as proprietary HTML-to-Markdown conversion, attachment handling limitations, and utilizes JXA/Bash scripting specific to macOS environments for seamless knowledge base integration.

Quick-reference card for the caveman skill suite: lists the caveman, ultracave and megacave reply modes, plus sub-skills for terse commits, one-line PR reviews, and markdown compression, with env-var and config-file setup.

This comprehensive toolkit automates core workflows within Apple Notes using JXA and Bash scripting. It allows users to batch-import content from Markdown files, generate structured notes using customizable templates (e.g., meeting minutes, daily logs), and automatically organize notes into designated folder hierarchies based on naming conventions. Ideal for knowledge workers managing large volumes of notes and content from diverse sources.