rules-distill

Extract cross-cutting principles from installed skill files into rule candidates.

Updated Apr 7, 2026

Search Tags:#automation #llm #skills #inventory #rules #scan #distillation

Ready to run

npx skills add https://github.com/semaes111/PROYECTO-SKILLS --skill rules-distill-semaes111

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: rules-distill
Source: https://github.com/semaes111/PROYECTO-SKILLS/tree/main/09-SKILLS-UTILIDADES/extraccion-reglas-distill
Command: npx skills add https://github.com/semaes111/PROYECTO-SKILLS --skill rules-distill-semaes111

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Centralizes and formalizes recurring practices found across many skills by scanning skill files and proposing rule candidates, eliminating ad-hoc knowledge scattered in individual skills.

Core Features & Use Cases

Deterministic inventory: Scripts enumerate installed skills and rules files to produce a complete factual index.
LLM cross-read judgment: An LLM analyzes clustered skills against existing rules to propose actionable verdicts (Append, Revise, New Section, New File, Already Covered, Too Specific).
User-driven execution: Presents candidates for review and requires explicit user approval before any rule modifications.
Use Case: Run after installing a batch of new skills or during monthly maintenance to surface principles that should be promoted to repository-level rules.

Quick Start

Run the rules-distill process to scan installed skills and generate rule candidates for user 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 common rules from multiple installed skill files?▼

To extract common rules from installed skill files, this Skill uses deterministic scripts to inventory skills and an LLM to cross-read clusters, proposing actionable rule candidates. It centralizes recurring practices scattered across individual files into formal rule proposals.

What is cross-cutting rule distillation for LLM skills?▼

Cross-cutting rule distillation is the process of scanning installed skill files to identify recurring principles and converting them into actionable rule candidates. It formalizes ad-hoc knowledge by promoting shared patterns to repository-level rules.

Do I need jq installed to scan skills and generate rule candidates?▼

Yes, you need jq installed as a dependency to run the deterministic inventory scripts that enumerate installed skills and rules files. The scripts rely on jq to produce the complete factual index required for the LLM cross-read judgment.

When should I run a rules maintenance scan on my skill inventory?▼

You should run a rules maintenance scan after installing new skills, during periodic monthly maintenance, or when audits reveal recurring patterns across multiple skills. This surfaces principles that should be promoted to repository-level rules.

Does the LLM automatically apply changes to existing rules files?▼

No, the LLM does not automatically apply changes to rules files. The Skill presents verdicts like Append, Revise, or New File as candidates and requires explicit user approval before any rule modifications are executed.

What is the best way to audit recurring patterns across installed skills?▼

The best way to audit recurring patterns is using deterministic scripts to inventory skills and rules, followed by an LLM cross-read to produce verdicts. This approach ensures a complete factual index before proposing any rule modifications.