rules-distill

Distill recurring principles from skills into formal rule candidates.

4|7|Updated Apr 9, 2026
One-click install
npx skills add https://github.com/arbisoft/ai-skillforge --skill rules-distill-arbisoft
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rules-distill
Source: https://github.com/arbisoft/ai-skillforge/tree/main/Claude/skills/rules-distill
Command: npx skills add https://github.com/arbisoft/ai-skillforge --skill rules-distill-arbisoft

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires jq, grep, sed, awk, date, stat, mktemp, find, bash, and includes scripts (resource) components.

What problem does it solve?

Distill cross-cutting principles from a growing set of skills into actionable rules to reduce duplication and improve consistency across governance.

Core Features & Use Cases

  • Inventory skills deterministically to identify overlapping principles.
  • Cross-read and categorize emerging patterns into rule candidates for existing files, new files, or revisions.
  • Produce a structured verdict set (Append, Revise, New Section, New File) with evidence and confidence for human approval.

Quick Start

Run the rules-distill workflow to inventory skills and generate initial rule candidates for review.

Frequently Asked Questions about rules-distill

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

FAQPage Schema
How do I extract cross-cutting principles from a large skill inventory?

To distill rules from an inventory, this process groups related skills to identify overlapping principles and generates a structured verdict set—such as appending, revising, or creating rule files—using an LLM-driven engine with provenance evidence.

What is the best way to generate actionable governance rules from existing automation skills?

Generating actionable rules requires cross-reading automation skills to identify recurring principles, categorizing them into candidates, and producing a structured verdict set with evidence and confidence for human review.

Do I need specific command-line tools to run cross-skill analysis for rule distillation?

Yes, distilling rules requires command-line dependencies including jq, grep, sed, awk, find, and bash to execute the deterministic inventory and scanning scripts needed for identifying overlapping principles.

When should I run a rules distillation workflow on my skill repository?

Run the rules distillation workflow during periodic maintenance or after installing new skills to identify emerging patterns, reduce duplication, and update a centralized rules corpus with actionable candidates.

How does LLM judgment work when creating a centralized rules corpus?

An LLM-driven verdict engine evaluates categorized rule candidates from deterministic scans, deciding to append, revise, or create new rule files with provenance evidence and confidence scores for human approval.