bmad-distillator

Lossless document compression reduces source files into dense, token-efficient formats optimized for LLM workflows. This process preserves all facts, decisions, and relationships, ensuring complete semantic fidelity while significantly decreasing prompt context size.

Semantic splitting divides large documents into coherent sections during compression, maintaining contextual extractability. You need it when processing extensive source files that exceed standard context limits, ensuring downstream LLM retrieval remains accurate and structurally intact.

To distill multiple source files, instruct the system to analyze and compress them into a single or multiple optimized documents. This workflow guarantees information integrity through optional validation stages, producing dense outputs ready for downstream AI retrieval.

Yes, validation and reconstruction features allow you to verify distillate integrity and reconstruct originals. This guarantees lossless compression for audit purposes or fallback, ensuring no critical facts or relationships are lost during the token-optimization process.

Yes, lossless compression is designed specifically for large-scale document workflows requiring maximized semantic fidelity and size efficiency. It optimizes diverse source documents into compact formats, making them ideal for retrieval-augmented generation and LLM context injection.