mh-distillator

Convert complex documents into concise summaries for LLM processing.

2|Updated Apr 5, 2026

Search Tags:#LLM optimization #information extraction #data summarization #document distillation #lossless compression

Ready to run

npx skills add https://github.com/Imad-Oute/MicroHard --skill mh-distillator

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: mh-distillator
Source: https://github.com/Imad-Oute/MicroHard/tree/main/src/core/mh-distillator
Command: npx skills add https://github.com/Imad-Oute/MicroHard --skill mh-distillator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The mh-distillator skill solves the problem of converting lengthy, complex documents into concise, token-efficient summaries that preserve essential information while being optimized for Large Language Model (LLM) consumption.

Core Features & Use Cases

Document Distillation: Converts multiple source documents into a single, hyper-compressed distillate.
Selective Output: Offers single-file or semantically split distillates based on content complexity.
Use Case: When reviewing extensive project documentation or research reports, this skill helps distill key information into a more digestible format for quick reference by LLMs.

Quick Start

To distill the contents of 'project-report.pdf', simply use the mh-distillator command.

Frequently Asked Questions about mh-distillator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I distill complex documents into concise summaries for LLM consumption?▼

Document distillation converts lengthy, complex source documents into concise, token-efficient summaries optimized for LLM consumption. It extracts key facts, decisions, constraints, and relationships while applying lossless compression techniques to preserve essential information.

What is lossless compression for document summarization?▼

Lossless compression for document summarization is the process of extracting key facts, decisions, and relationships from complex documents and organizing them into efficient formats. This ensures all essential information is preserved without losing critical context for LLM processing.

Can I extract key facts and decisions from multiple project reports into a single file?▼

Yes, you can distill multiple source documents into a single hyper-compressed distillate. The process extracts key facts, decisions, constraints, and relationships, offering either a single-file or semantically split output based on content complexity.

Does mh-distillator work with project documentation and research reports?▼

Yes, mh-distillator works with extensive project documentation and research reports. It hyper-compresses these complex documents into digestible formats, organizing extracted key information efficiently for quick reference by LLMs.

What is the best way to optimize lengthy documents for LLM context windows?▼

The best way to optimize lengthy documents for LLM context windows is applying lossless compression techniques to extract key facts and relationships. This organizes information into token-efficient, concise summaries suitable for LLM processing.