content-quality-auditor

aaron-he-zhu/seo-geo-claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/aaron-he-zhu/seo-geo-claude-skills --skill content-quality-auditor
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summary

Comprehensive 80-item content quality audit across CORE-EEAT dimensions with prioritized improvement plan.

  • Evaluates content against 8 dimensions: Contextual Clarity, Organization, Referenceability, Exclusivity (CORE, GEO-focused) plus Experience, Expertise, Authoritativeness, Trust (EEAT, SEO-focused)
  • Produces GEO Score, SEO Score, content-type weighted total, per-item pass/partial/fail ratings, and veto item checks for critical trust violations
  • Generates Top 5 prioritized improveme
skill.md

Content Quality Auditor

Based on CORE-EEAT Content Benchmark. Full benchmark reference: references/core-eeat-benchmark.md

SEO & GEO Skills Library · 20 skills for SEO + GEO · ClawHub · skills.sh System Mode: This cross-cutting skill is part of the protocol layer and follows the shared Skill Contract and State Model.

This skill evaluates content quality across 80 standardized criteria organized in 8 dimensions. It produces a comprehensive audit report with per-item scoring, dimension and system scores, weighted totals by content type, and a prioritized action plan.

System role: Publish Readiness Gate. It decides whether content is ready to ship, what blocks publication, and what should be promoted into durable project memory.

When This Must Trigger

Use this when content needs a quality check before publishing — even if the user doesn't use audit terminology:

  • User asks "is this ready to publish" or "how good is this"
  • User just finished writing with seo-content-writer or content-refresher
  • PostToolUse hook auto-triggers: after content is written or substantially edited, the hook recommends this audit. When hook-triggered, skip setup questions — audit the content that was just produced.
  • Auditing content quality before publishing
  • Evaluating existing content for improvement opportunities
  • Benchmarking content against CORE-EEAT standards
  • Comparing content quality against competitors
  • Assessing both GEO readiness (AI citation potential) and SEO strength (source credibility)
  • Running periodic content quality checks as part of a content maintenance program
  • After writing or optimizing content with seo-content-writer or geo-content-optimizer

What This Skill Does

  1. Full 80-Item Audit: Scores every CORE-EEAT check item as Pass/Partial/Fail
  2. Dimension Scoring: Calculates scores for all 8 dimensions (0-100 each)
  3. System Scoring: Computes GEO Score (CORE) and SEO Score (EEAT)
  4. Weighted Totals: Applies content-type-specific weights for final score
  5. Veto Detection: Flags critical trust violations (T04, C01, R10)
  6. Priority Ranking: Identifies Top 5 improvements sorted by impact
  7. Action Plan: Generates specific, actionable improvement steps

Quick Start

Start with one of these prompts. Finish with a publish verdict and a handoff summary using the repository format in Skill Contract.

Audit Content

Audit this content against CORE-EEAT: [content text or URL]
Run a content quality audit on [URL] as a [content type]

Audit with Content Type

CORE-EEAT audit for this product review: [content]
Score this how-to guide against the 80-item benchmark: [content]

Comparative Audit

Audit my content vs competitor: [your content] vs [competitor content]

Skill Contract

Gate verdict: SHIP (no veto items, dimension scores above threshold) / FIX (issues found but no veto) / BLOCK (veto item T04, C01, or R10 failed). Always state the verdict prominently at the top of the report.

Expected output: a CORE-EEAT audit report, a publish-readiness verdict, and a short handoff summary ready for memory/audits/content/.

  • Reads: the target content, content type, supporting evidence, and any prior decisions from CLAUDE.md and the shared State Model when available.
  • Writes: a user-facing audit report plus a reusable summary that can be stored under memory/audits/content/.
  • Promotes: veto items and publish blockers to memory/hot-cache.md (auto-saved, no user confirmation needed). Top improvement priorities to memory/open-loops.md.
  • Next handoff: use the Next Best Skill below once the verdict is clear.

Data Sources

See CONNECTORS.md for tool category placeholders.

With ~~web crawler + ~~SEO tool connected: Automatically fetch page content, extract HTML structure, check schema markup, verify internal/external links, and pull competitor content for comparison.

With manual data only: Ask the user to provide:

  1. Content text, URL, or file path
  2. Content type (if not auto-detectable): Product Review, How-to Guide, Comparison, Landing Page, Blog Post, FAQ Page, Alternative, Best-of, or Testimonial
  3. Optional: competitor content for benchmarking

Proceed with the full 80-item audit using provided data. Note in the output which items could not be fully evaluated due to missing access (e.g., backlink data, schema markup, site-level signals).

Decision Gates

When stopping to ask, always: (1) state the specific value and threshold, (2) offer numbered options with outcomes.

Stop and ask the user when:

  • Content is under minimum word count for its type (blog/guide: 300 words; product/landing page: 150 words; FAQ: fewer than 3 entries with 50+ words each) — state the actual count and offer: (1) expand to minimum, (2) continue audit with Insufficient Data flags, (3) cancel
  • Content type cannot be auto-detected — state what you detected and ask to confirm before proceeding
  • Content is primarily media (video/image) with minimal text — ask whether to audit transcript, alt text, or skip
  • More than 50% of a dimension's items are N/A — name the dimension and ask: (1) provide supplementary data, (2) mark entire dimension as Insufficient Data
  • Any veto item triggers — flag it immediately with the item ID and ask: (1) stop for immediate fix, (2) continue full audit and flag in report

Continue silently (never stop for):

  • Individual Partial scores within a dimension
  • Missing SEO tool data (mark items as N/A and continue)
  • Low overall score (the report is the deliverable, not a judgment call)
  • User not specifying content type (auto-detect and state your assumption)

Instructions

When a user requests a content quality audit:

Step 1: Preparation

### Audit Setup

**Content**: [title or URL]
**Content Type**: [auto-detected or user-specified]
**Dimension Weights**: [loaded from content-type weight table]

#### Veto Check (Emergency Brake)

| Veto Item | Status | Action |
|-----------|--------|--------|
| T04: Disclosure Statements | ✅ Pass / ⚠️ VETO | [If VETO: "Add disclosure banner at page top immediately"] |
| C01: Intent Alignment | ✅ Pass / ⚠️ VETO | [If VETO: "Rewrite title and first paragraph"] |
| R10: Content Consistency | ✅ Pass / ⚠️ VETO | [If VETO: "Verify all data before publishing"] |

If any veto item triggers, flag it prominently at the top of the report and recommend immediate action before continuing the full audit.

Step 2: CORE Audit (40 items)

Evaluate each item against the criteria in references/core-eeat-benchmark.md.

Score each item:

  • Pass = 10 points (fully meets criteria)
  • Partial = 5 points (partially meets criteria)
  • Fail = 0 points (does not meet criteria)
### C — Contextual Clarity

| ID | Check Item | Score | Notes |
|----|-----------|-------|-------|
| C01 | Intent Alignment | Pass/Partial/Fail | [specific observation] |
| C02 | Direct Answer | Pass/Partial/Fail | [specific observation] |
| ... | ... | ... | ... |
| C10 | Semantic Closure | Pass/Partial/Fail | [specific observation] |

**C Score**: [X]/100

Repeat the same table format for O (Organization), R (Referenceability), and E (Exclusivity), scoring all 10 items per dimension.

Step 3: EEAT Audit (40 items)

### Exp — Experience

| ID | Check Item | Score | Notes |
|----|-----------|-------|-------|
| Exp01 | First-Person Narrative | Pass/Partial/Fail | [specific observation] |
| ... | ... | ... | ... |

**Exp Score**: [X]/100

Repeat the same table format for Ept (Expertise), A (Authority), and T (Trust), scoring all 10 items per dimension.

See references/item-reference.md for the complete 80-item ID lookup table and site-level item handling notes.

Step 4: Scoring & Report

Calculate scores and generate the final report:

## CORE-EEAT Audit Report

### Overview

- **Content**: [title]
- **Content Type**: [type]
- **Audit Date**: [date]
- **Total Score**: [score]/100 ([rating])
- **GEO Score**: [score]/100 | **SEO Score**: [score]/100
- **Veto Status**: ✅ No triggers / ⚠️ [item] triggered

### Dimension Scores

| Dimension | Score | Rating | Weight | Weighted |
|-----------|-------|--------|--------|----------|
| C — Contextual Clarity | [X]/100 
how to use content-quality-auditor

How to use content-quality-auditor on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add content-quality-auditor
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aaron-he-zhu/seo-geo-claude-skills --skill content-quality-auditor

The skills CLI fetches content-quality-auditor from GitHub repository aaron-he-zhu/seo-geo-claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/content-quality-auditor

Reload or restart Cursor to activate content-quality-auditor. Access the skill through slash commands (e.g., /content-quality-auditor) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.755 reviews
  • Noah Jackson· Dec 20, 2024

    I recommend content-quality-auditor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Ama Park· Dec 16, 2024

    content-quality-auditor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Xiao Torres· Dec 16, 2024

    Keeps context tight: content-quality-auditor is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Soo Farah· Dec 4, 2024

    Useful defaults in content-quality-auditor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aditi Patel· Nov 23, 2024

    I recommend content-quality-auditor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Valentina Chen· Nov 11, 2024

    Useful defaults in content-quality-auditor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Soo Nasser· Nov 7, 2024

    content-quality-auditor has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Jin Abebe· Nov 7, 2024

    Registry listing for content-quality-auditor matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aditi Sethi· Oct 26, 2024

    content-quality-auditor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Mateo Malhotra· Oct 26, 2024

    Useful defaults in content-quality-auditor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

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