10x-rule-review

Reviews AI rules files and produces a five-check scorecard with concrete fixes.

Updated Jul 4, 2026
One-click install
npx skills add https://github.com/Assamir/ai-toolkit --skill 10x-rule-review-assamir
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: 10x-rule-review
Source: https://github.com/Assamir/ai-toolkit/tree/main/.cursor/skills/10x-rule-review
Command: npx skills add https://github.com/Assamir/ai-toolkit --skill 10x-rule-review-assamir

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI rules files like CLAUDE.md, AGENTS.md, or .cursor/rules/*.mdc often grow bloated, vague, and poorly ordered, which wastes context window space and causes agents to ignore critical instructions. This Skill audits any rules-for-AI markdown file and returns a structured scorecard with actionable fixes. ## Core Features & Use Cases - Five-dimension audit: Scores length, direct code snippets, vague language, redundant knowledge, and rule ordering with OK/WARN/FAIL verdicts. - Grounded rewrites: Translates vague phrases like "write clean code" into testable rules based on the project's actual stack and conventions. - Interactive reordering: Detects buried critical rules and, with explicit user approval, reorders sections so high-priority rules sit where models pay the most attention. - Use Case: A developer suspects their 600-line AGENTS.md is being ignored by their coding agent. They run the review, get a scorecard showing FAIL on length and ordering, and apply the top three fixes. ## Quick Start Ask the AI to review your rules file, for example: "Review my AGENTS.md and score it" or "Audit @CLAUDE.md for problems".

Frequently Asked Questions about 10x-rule-review

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

FAQPage Schema
How do I review my CLAUDE.md or AGENTS.md file?

Pass the file path as an argument, such as @CLAUDE.md, AGENTS.md, or .cursor/rules/api.mdc. The skill reads the file, runs five checks, and prints a scorecard with verdicts and concrete fixes for each finding.

What does the AI rules review check for?

It runs five checks: file length, direct code or config snippets, vague untestable language, redundant knowledge the model already knows, and rule ordering. Each check returns an OK, WARN, or FAIL verdict with line-referenced findings.

Does the rule review work with .cursor/rules .mdc files?

Yes, it treats .mdc files like any other rules-for-AI markdown. Frontmatter such as globs and alwaysApply is treated as configuration, and rule lines are counted from after the frontmatter block.

Will the review edit or rewrite my rules file?

No, the default output is read-only. The only possible edit is a section reorder from Check 5, and that happens only after you explicitly approve the proposed order through an interactive prompt.

Why does rule ordering matter in an AI instructions file?

Models pay more attention to the start and end of long contexts, so critical rules buried in the middle are statistically less likely to be followed. The review flags files where hard rules appear after line 200 or where intro content dominates the top.

What are the limitations of the rules file audit?

It scores the condition of the rule artifact, not the project's architecture or tech choices. It never rewrites rule content, generates a fixed version of the file, or merges scorecards when multiple files are reviewed.