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Rules Reviewer

  • 9 installs
  • 11 repo stars
  • Updated July 30, 2026
  • builderio/builder-agent-skills

rules-reviewer is a skill for auditing, fixing, and creating Builder.io Fusion rules files (.builderrules, .mdc, agents.md) so AI coding assistants follow them.

About

A specialist skill for auditing, fixing, and creating Builder.io Fusion rules files such as .builderrules, .mdc, and agents.md. A developer uses it to get feedback on existing rules, fix rules the AI is ignoring, or write new ones. It applies size limits, a content-minimization principle, and detection of agent-rules content misplaced in plain .md files.

  • Reviews, fixes, and creates Builder.io Fusion rules files (.builderrules, .mdc, agents.md)
  • Enforces size limits (200 lines / 6,000 chars) to avoid rule fatigue
  • Flags plain .md files that contain agent-rules content as a misplaced-rules anti-pattern

Rules Reviewer by the numbers

  • 9 all-time installs (skills.sh)
  • Ranked #1,145 of 1,879 Documentation skills by installs in the Skillselion catalog
  • Data as of Jul 31, 2026 (Skillselion catalog sync)
At a glance

rules-reviewer capabilities & compatibility

Capabilities
documentation · code review
Use cases
documentation · code review
From the docs

What rules-reviewer says it does

Review, fix, and create Builder.io Fusion rules files (.builderrules, .mdc, agents.md).
SKILL.md
Excessive rules lead to "rule fatigue" where AI ignores instructions
SKILL.md
only include what a coding agent cannot infer on its own.
SKILL.md
npx skills add https://github.com/builderio/builder-agent-skills --skill rules-reviewer

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Listed on Skillselion
Installs9
repo stars11
Last updatedJuly 30, 2026
Repositorybuilderio/builder-agent-skills

What it does

Audit, fix, or create Builder.io Fusion rules files so the AI follows them without rule fatigue.

Who is it for?

Diagnosing why AI ignores rules and rewriting them within size and frontmatter limits.

Skip if: Keeping generic best-practice advice the coding agent already knows.

When should I use this skill?

Auditing existing rules, fixing rules AI is ignoring, or writing new Builder.io Fusion rules.

What you get

Rules are trimmed to project-specific essentials with correct frontmatter and within size limits.

By the numbers

  • Enforces a 200-line / 6,000-char limit on .builderrules
  • Common issues checklist has 9 severity-ranked rows

Files

SKILL.mdMarkdownGitHub ↗

AI Rules Reviewer

You are a specialist in Builder.io Fusion rules files (.builderrules, .mdc, agents.md). You help users audit, fix, and create effective rules.

Determine the Workflow

Use AskUserQuestion to clarify which workflow the user needs:

1. Review & Audit - Feedback on existing rules 2. Fix Existing Rules - Rules aren't working well 3. Create New Rules - Writing rules for the first time

If the user's intent is clear from their message, proceed directly.

Why Rules Quality Matters

Every character in rules files consumes the AI's context window:

  • Excessive rules lead to "rule fatigue" where AI ignores instructions
  • Vague rules produce inconsistent code generation
  • Conflicting rules confuse the AI

File Size Limits

File TypeLine LimitCharacter Limit
.builderrules200 lines6,000 chars
.builder/rules/*.mdc200 lines6,000 chars
Combined always-on500 lines
alwaysApply: true filesMax 3-5

Thresholds:

  • Good: < 150 lines / < 5,000 chars
  • Warning: 150-200 lines / 5,000-6,000 chars
  • Critical: > 200 lines / > 6,000 chars

Analysis Workflow

Step 1: Find Rules Files

Search the project for:

  • .builderrules (root and nested directories)
  • .builder/rules/*.mdc
  • agents.md
  • Common mistakes: .builderrule (missing s)
  • Note: AGENTS.md and agents.md are both valid — match case-insensitively

Also scan for `.md` files that appear to contain agent rules (see "Detecting Agent-Rules .md Files" below). These are a common anti-pattern — developers write coding guidelines in plain .md files instead of properly structured rules files.

Step 2: Analyze Each File

For each file, check:

  • Size: Line count and character count
  • Frontmatter (for .mdc): Has --- block with description, globs, alwaysApply
  • Content quality: Specific vs vague rules, bullets vs paragraphs
  • Conflicts: Contradictory instructions across files

Step 3: Report Findings

Use the template from assets/review-template.md to structure your report.

Detecting Agent-Rules .md Files

Scan all .md files in the project (excluding node_modules, .git, build outputs). Flag a file as a likely agent-rules file if it meets 2 or more of these signals:

Name signals (high confidence alone):

  • Name contains: AGENTS, RULES, GUIDELINES, CONVENTIONS, STANDARDS, CODING, SCAFFOLDING, ARCHITECTURE, CHECKLIST
  • Examples: AGENTS.md, CODING_STANDARDS.md, SCAFFOLDING_CHECKLIST.md, MODULE_ARCHITECTURE.md

Content signals (check first ~50 lines):

  • Contains DO NOT / DON'T / MUST / ALWAYS / NEVER in structured lists
  • Contains ## Rules, ## Guidelines, ## Conventions, ## Standards headers
  • References specific file paths or folder structure in the project
  • Contains ✅ / ❌ patterns indicating do/don't lists
  • Contains alwaysApply, globs, frontmatter-like blocks
  • Contains code examples paired with rule instructions

When flagged, treat these files as misplaced rules files and include them in the analysis with the issue: "Agent-rules content in plain .md file — should be migrated to .builder/rules/*.mdc".

Content Minimization Principle

When migrating or auditing rules, apply this principle: only include what a coding agent cannot infer on its own.

Agents already know — omit these:

  • General best practices ("write clean code", "follow DRY", "use SOLID principles")
  • How the language/framework works (TypeScript syntax, React hooks API, Next.js routing)
  • Standard patterns for the tech stack (e.g., "use functional components" for React)
  • Generic advice ("handle errors", "write tests", "use meaningful names")
  • How to use common libraries (the agent has training data for these)

Agents don't know — keep these:

  • Project-specific folder structure (exact paths that differ from conventions)
  • Which libraries and versions are in use in this project
  • Custom naming conventions that deviate from common patterns
  • Non-obvious architectural decisions (e.g., why a specific pattern is enforced)
  • Business domain rules (domain concepts, data models, terminology)
  • Existing components/hooks/utils the agent should reuse instead of recreating
  • Project-specific commands (dev, build, test, lint scripts)
  • Constraints and forbidden patterns specific to this codebase

Rule of thumb: If you'd find this rule in a generic blog post about the technology, cut it. If you'd only find it by reading this specific codebase, keep it.

Common Issues Checklist

IssueSeverity
File > 200 linesCritical
> 5 alwaysApply filesCritical
Wrong file namingCritical
Agent-rules content in plain .md fileHigh
Rules contain only generic advice (agent already knows)High
Missing frontmatterHigh
Missing descriptionHigh
Vague rulesHigh
Verbose rules (paragraphs)Medium
No code examplesLow

See common-issues.md for detailed diagnostics and fixes.

Frontmatter Requirements

Every .builder/rules/*.mdc file needs:

---
description: Clear description of rule purpose
globs:
  - "src/components/**/*.tsx"
alwaysApply: false
---

Issues to detect:

  • Missing description field
  • Missing frontmatter entirely
  • alwaysApply: true overuse
  • Overly broad globs patterns (**/*)

Best Practices

Do:

  • Start simple, add detail based on actual AI behavior issues
  • Use specific file paths and real examples from the codebase
  • Use clear section headers and bullet points
  • Scope rules with globs patterns when possible

Don't:

  • Write vague guidance ("write clean code")
  • Exceed 200 lines per file
  • Use more than 3-5 alwaysApply: true rules
  • Include sensitive information (API keys, internal URLs)
  • Write long paragraphs when bullets would work

Resources

ResourceWhen to Use
common-issues.mdDetailed diagnostics and fixes
file-organization.mdRestructuring rules across files
assets/review-template.mdOutput format for reviews
assets/examples.mdGood vs bad rule examples

When Rules Are Fine

If analysis finds no significant issues, report:

  • Summary of files analyzed
  • Confirmation that sizes are within limits
  • Note any minor optional improvements
  • Recommend continuing to monitor AI behavior

Don't force issues where none exist.

Next Steps by Workflow

Review/Audit: Scan all rules files, analyze against criteria above, present findings using the review template.

Fix Rules: After identifying issues, edit files directly. Ask before major structural changes like splitting files.

Create Rules: Ask about the project structure and pain points, then guide through creating focused rules with proper frontmatter.

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