bmad-distillator

Compress multiple source documents into a lossless, token-efficient distillate.

Updated Mar 18, 2026

Search Tags:#llm #compression #document-processing #token-efficiency #information-extraction #distillate

Ready to run

npx skills add https://github.com/AhmedKaram50/research --skill bmad-distillator-ahmedkaram50

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: bmad-distillator
Source: https://github.com/AhmedKaram50/research/tree/main/shopify-builder/_bmad/core/skills/bmad-distillator
Command: npx skills add https://github.com/AhmedKaram50/research --skill bmad-distillator-ahmedkaram50

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This skill enables lossless compression of multiple source documents into a single, token-efficient distillate. It preserves every fact, decision, constraint, and relationship while removing overhead for LLM-friendly context.

Core Features & Use Cases

Deterministic, lossless compression that preserves all source information
Supports routing, grouping, and optional semantic splitting for large inputs
Round-trip validation is available when requested to ensure fidelity across transformations

Quick Start

Provide one or more source document paths and optional parameters to generate a distillate using the activation flow.

Frequently Asked Questions about bmad-distillator

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

FAQPage Schema

How do I compress multiple documents into a single token-efficient output for LLM context?▼

To compress multiple documents into a single token-efficient output, provide source document paths and an optional token budget. The process generates a lossless distillate that preserves all source facts for LLM-friendly context.

What is lossless document distillation and how does it preserve source information?▼

Lossless document distillation is a compression technique that removes overhead while preserving every fact, decision, constraint, and relationship from the source documents. It ensures deterministic, source-preserving compression for downstream workflows.

Can I validate that my compressed distillate retains all the original information?▼

You can validate your compressed distillate by using the --validate flag. This triggers round-trip checks to ensure fidelity across transformations, verifying that all original source information is retained.

Does document compression support grouping and splitting for large inputs?▼

Document compression supports routing, grouping, and optional semantic splitting for large inputs. This allows you to manage multiple source documents efficiently while maintaining deterministic, source-preserving compression.

What inputs do I need to generate a token-efficient distillate from my files?▼

To generate a token-efficient distillate, you need input paths via source_documents and optional parameters including downstream_consumer, token_budget, output_path, and a --validate flag for round-trip checks.