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  • 1
    Planning with Files

    Planning with Files

    Claude Code skill implementing Manus-style persistent planning

    Planning With Files is a Claude Code skill — essentially a plugin for AI agent workflows — that adapts the “Manus-style” persistent markdown planning methodology into developer workflows, enabling structured project planning, progress tracking, and knowledge storage using plain text files. Inspired by high-profile agent workflows and context engineering patterns, it uses persistent markdown files (like task_plan.md, progress.md, and findings.md) as the “working memory” for AI agents,...
    Downloads: 7 This Week
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  • 2
    Remarkable for Linux

    Remarkable for Linux

    The Markdown Editor for Linux

    With Live Preview you can see your changes as you make them. There is no need to export first to check your syntax. This is accompanied by synchronized scrolling. Remarkable has Github Flavoured Markdown. This has a simple, easy-to-learn syntax with features like checklists, highlighting, links, images and more. Remarkable allows you to export your files to PDF and HTML from within the app. The HTML code is even prettified and PDFs have a TOC. You can style your markdown documents however...
    Downloads: 1 This Week
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  • 3
    Jupytext

    Jupytext

    Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts

    Have you always wished Jupyter notebooks were plain text documents? Wished you could edit them in your favorite IDE? And get clear and meaningful diffs when doing version control? Then, Jupytext may well be the tool you’re looking for. Only the notebook inputs (and optionally, the metadata) are included. Text notebooks are well suited for version control. You can also edit or refactor them in an IDE - the .py notebook above is a regular Python file. Text notebooks with a .py or .md extension...
    Downloads: 0 This Week
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  • 4
    ARIS

    ARIS

    Lightweight Markdown-only skills for autonomous ML research

    ARIS is an experimental automation framework that leverages AI coding agents to perform continuous research and development tasks autonomously, even without active user supervision. The system is designed to run iterative cycles of research, coding, testing, and refinement, effectively simulating a “sleep mode” where productive work continues in the background. It integrates with AI tools such as Claude Code to generate solutions, analyze results, and improve outputs over time. The project...
    Downloads: 0 This Week
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