System Documentation

What problem does it solve?

It prevents AI-driven rule changes from being based on missing evidence or overly broad matches by requiring concrete source artifacts, validator/receipt proof, and scoped target verification during rule application.

Core Features & Use Cases

  • Evidence-driven rule validation: Checks rule frontmatter, registry entries, scope, and dry-run hit behavior before accepting usefulness or applicability.
  • Safe, bounded application decisions: Produces a structured rule-application-report with PASS/FAIL/PARTIAL/BLOCKED and clear nextAction instead of guessing.
  • False-positive and overreach control: Isolates the smallest noisy rule text and reviews protected-block simplification risk to avoid unsafe edits.

Quick Start

Ask your AI tool to run rule-application in review mode for your codebase and return a rule-application-report with blocked reasons if any required evidence or receipts are missing.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: rule-application
Download link: https://github.com/vTRKA/supervibe/archive/main.zip#rule-application

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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