distill

Distill documents into five granularity levels with critical_loss and tokens_after metrics.

Updated Aug 27, 2026

Search Tags:#content #distill #natural-language #granularity #token-reduction #loss-estimation #data-compression

Ready to run

npx skills add https://github.com/gudzenkov/SuperClaudeZero --skill distill-gudzenkov

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: distill
Source: https://github.com/gudzenkov/SuperClaudeZero/tree/main/.claude/skills/distill
Command: npx skills add https://github.com/gudzenkov/SuperClaudeZero --skill distill-gudzenkov

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, claude_agent_sdk, and includes scripts (resource) components.

What problem does it solve?

Distill content to a compact form while preserving core meaning, enabling faster review and decision-making.

Core Features & Use Cases

Granular distillation: Choose among five levels (essence to minimal) to control the amount of content retained.
Quality loss estimation: Preview expected information loss before applying changes.
Safe workflow: Validate the scope of distillation to protect critical details.

Quick Start

Distill the attached content to a chosen granularity level and review the estimated quality loss before execution.

Frequently Asked Questions about distill

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

FAQPage Schema

How do I distill content to reduce token size while preserving core meaning?▼

Distill content by selecting one of five granularity levels to control information density, allowing you to reduce document size while preserving essential meaning for faster review.

Can I estimate information loss before applying natural-language data compression?▼

You can preview expected quality loss before execution by reviewing the estimated critical_loss and tokens_after metrics, ensuring safe validation of critical details before distillation.

What is the best way to summarize policies and code comments with adjustable granularity?▼

Granular distillation provides five levels ranging from essence to minimal, specifically designed to compactly distill policies, memos, code comments, and similar documents.

Does the distillation workflow validate input scope to protect critical details?▼

The workflow validates input scope through dedicated scripts to protect critical details, ensuring safe content reduction and preventing unintended loss of essential information.

How do I control information density when compressing natural-language documents?▼

Control information density by choosing among five levels of granular distillation, which directly adjusts the amount of content retained and provides measurable quality loss estimation.

When do I need loss estimation for content reduction?▼

Loss estimation is needed when distilling critical documents like policies or memos, as it reveals the expected critical_loss and tokens_after metrics to validate safety before execution.