<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> Knowledge Absorber is an AI skill module designed as an "external brain" for AI assistants, enabling them to deeply parse lengthy documents and generate structured knowledge crystals in Markdown and HTML formats. It targets users dealing with high-cognitive-load tasks like processing extensive technical documentation or ancient texts, providing an "all-around tutor-level" analysis and note-taking capability.

How It Works

The module employs a folder-level plug-and-play design, allowing integration with various AI assistants (Trae, Claude, Gemini, VS Code Copilot) by simply renaming a configuration directory (e.g., .trae to .claude). It processes inputs via an ingestion pipeline, followed by "lens analysis" defined in SKILL.md (e.g., Mechanical Lens, Meaning Lens), and delivers structured outputs. Novel features include the "Deep Fission" module for atomic contradiction analysis and version verification, and an upgraded "Strict Filter" for focused HTML content viewing.

Quick Start & Requirements

• Primary install: Ensure Python 3.8+ is installed. Navigate to the knowledge-absorber directory and run pip install -r requirements.txt.
• Prerequisites: Python 3.8+.
• Setup: Integration involves renaming the project's configuration folder (e.g., .trae) to match the target AI assistant's convention (e.g., .claude, .gemini, .vscode).
• Relevant pages: CHANGELOG.md, README_EN.md.

Highlighted Details

• AI Integration: Seamlessly integrates with multiple AI assistants via a simple folder renaming convention for plug-and-play functionality.
• Advanced Analysis: Features a "Deep Fission" module for atomic contradiction analysis and version verification, designed to uncover counter-intuitive conclusions.
• Content Processing: Supports multi-link/file synchronization, with an upgraded "Strict Filter" in HTML views that hides non-matching content for focused reading.
• Output Formats: Generates detailed Markdown notes (.md) and visually appealing HTML cards (.html) suitable for archiving and sharing, supporting dark/light modes and Mermaid diagrams.
• Customization: Core logic and AI behavior are configurable via the SKILL.md file, allowing users to modify parsing depth and output styles.

Maintenance & Community

• Maintainer: Little Code Sauce.
• No community links (Discord/Slack, etc.) or roadmap details were found in the provided README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: Compatible with Python 3.8+. The MIT license generally permits commercial use and closed-source linking.

Limitations & Caveats

This module is specifically designed for "high cognitive load" scenarios and is not intended for simple search queries. Customization of AI behavior requires direct editing of the SKILL.md file. No explicit mention of alpha status, known bugs, or deprecations was found.