10x-rule-review

Scores AI rules markdown files on five axes with a structured, line-referenced report.

1|Updated Feb 26, 2025
One-click install
npx skills add https://github.com/kryptonum-dev/fabryka-atrakcji --skill 10x-rule-review
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 10x-rule-review
Source: https://github.com/kryptonum-dev/fabryka-atrakcji/tree/main/.agents/skills/10x-rule-review
Command: npx skills add https://github.com/kryptonum-dev/fabryka-atrakcji --skill 10x-rule-review

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you assess whether an AI rules file is in good operational condition, so agents follow the right instructions reliably instead of wasting context on noise.

Core Features & Use Cases

  • Five-axis rule health scorecard: Length, snippet/config issues, vague language, redundancy, and attention-friendly ordering.
  • Concrete, actionable fixes: Identifies specific problems and suggests testable improvements rather than generic advice.
  • Optional reorder guidance: Proposes a better section order and can request explicit approval before any changes.

Quick Start

Ask the skill to review a specific rules markdown file by providing its path to AGENTS.md (or another rules file).

Frequently Asked Questions about 10x-rule-review

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

FAQPage Schema
How do I audit an AGENTS.md file for AI agent instruction quality?

Auditing AI rule files involves scoring condition across five axes: length, inline snippet drift, vague language, redundancy, and attention-aware ordering. This produces a structured scorecard with line-referenced findings for fixing AGENTS.md files.

What is the best way to fix vague or unenforceable language in Copilot instructions?

Fixing vague Copilot instructions requires identifying unenforceable language through a markdown review. A five-axis audit pinpoints specific lines and proposes testable, concrete improvements to make agent instructions reliable.

Can I check for inline config drift in my .cursor rules file?

Yes, checking for inline config drift in .cursor rules involves reviewing the markdown artifact for snippet inconsistencies. The audit reports exact line references to help resolve config drift issues.

Does the rules audit automatically edit and reorder my repository markdown files?

No, the rules audit does not automatically edit repository markdown files. It reads the full file, reports a structured scorecard, and optionally proposes a section reorder, requiring explicit user approval before making any changes.

Why are my AI agents ignoring instructions in nested per-area markdown files?

AI agents ignore instructions in nested markdown files when rules suffer from poor attention-aware ordering, excessive length, or redundancy. A five-axis markdown review identifies these structural issues with line-referenced findings.