anti-distill

Markdown sanitization for external sharing works by identifying core knowledge to remove or generalize while preserving structural elements like headings and formatting. This produces a publication-ready file that reveals only non-sensitive information suitable for external handoff.

Anti-distillation in knowledge management is a data cleaning process that removes or generalizes sensitive insights from Skill documents. It ensures public or audited versions reveal only non-sensitive structural information while non-public content is properly masked.

Yes, you can clean Skill content for public audits while keeping the original document structure. The process reforms content by replacing sensitive details but retains Markdown formatting, headings, and non-sensitive content for seamless handoff.

The best way to prepare sanitized Skill drafts is to apply anti-distillation processing to the content. This reads the file, identifies core knowledge to remove or generalize, and outputs a cleaned version that looks complete but has sensitive insights properly masked.

Generalized documentation looks complete but reveals no sensitive insights because the cleaning process specifically extracts core knowledge to remove or mask. It preserves the document's structural appearance while replacing non-public content with generalized statements.