bmad-distillator

You can compress LLM context documents without losing facts by distilling them into a dense, token-efficient distillate. This process preserves all discrete data points, constraints, relationships, and open questions while removing formatting overhead and noise.

Document distillation is the process of extracting all essential facts, decisions, and relationships from source documents into a single dense distillate. It reduces token usage by stripping formatting overhead and noise while staging and validating the compressed output for downstream workflows.

Yes, you can distill multiple mixed-document inputs into a single lossless distillate. The process extracts facts, decisions, and relationships across all provided sources while generating portable frontmatter with source tracking and token estimates.

You can split large documents semantically by producing section distillates instead of a single output. This approach supports stage-based compression and validation, enabling complex pipelines to process distinct semantic sections independently.

Yes, lossless document compression supports downstream LLM pipeline staging through semantic stitching and validation. It produces a portable distillate with frontmatter containing sources and token estimates, ensuring all facts and constraints remain intact for subsequent tasks.