bmad-distillator

Compresses source documents into a lossless, token-efficient format for LLM consumption.

Updated Mar 16, 2026

Search Tags:#document processing #knowledge management #llm #compression #information extraction #distillation

Ready to run

npx skills add https://github.com/deltatree/wissensmanagement --skill bmad-distillator-deltatree

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bmad-distillator
Source: https://github.com/deltatree/wissensmanagement/tree/main/_bmad/core/skills/bmad-distillator
Command: npx skills add https://github.com/deltatree/wissensmanagement --skill bmad-distillator-deltatree

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of feeding large, human-readable documents into LLMs efficiently without losing critical information, by creating highly compressed, token-optimized distillates.

Core Features & Use Cases

Lossless Compression: Preserves all facts, decisions, and relationships from source documents.
LLM Optimization: Strips human-centric overhead, making documents ideal for LLM context windows.
Use Case: Distill a lengthy technical specification document into a concise format that an AI can fully process to generate a summary or answer detailed questions, ensuring no critical requirement is missed.

Quick Start

Use the bmad-distillator skill to distill the document located at '/path/to/my/document.md'.

Frequently Asked Questions about bmad-distillator

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

FAQPage Schema

How do I compress large documents for LLM context windows without losing information?▼

Lossless document compression strips human-centric overhead from source files to create token-efficient distillates optimized for LLM consumption. This preserves all facts, decisions, and relationships while fitting large documents into LLM context windows.

What is lossless document distillation and when do I need it?▼

Document distillation compresses human-readable text into a token-optimized format for AI processing. You need it when feeding lengthy technical specifications into LLMs to ensure no critical requirements are missed during summarization or question answering.

Can I process multiple input files and set a specific token budget for LLM compression?▼

Yes, this compression handles single or multiple input files and supports optional downstream consumer context with defined token budgets. This allows precise control over the final distillate size for specific LLM constraints.

How do I verify that distillation preserves all original facts?▼

A validation flag enables round-trip reconstruction testing to verify lossless document compression. This tests the agent-based compression scripts to ensure all critical information and relationships are fully preserved from the source.

Does this document compression tool require Python to run?▼

Yes, the lossless distillation operates via Python scripts for document analysis and agent-based compression. You need a Python environment to execute the compression and validation processes.