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Eeat Content Quality Audit

Community
jiaxiaojunQAQ
eeat-content-quality-audit

Systematic content quality audit based on 80 CORE-EEAT standards, evaluating content's GEO (Generative Engine Optimization) and SEO (Search Engine Optimization) potential. Features 8-dimension scoring, weighted total calculation, veto item detection, and priority improvement recommendations. Applicable for pre-publication checks, competitive analysis, and AI citation potential assessment.

Overview

PublisherjiaxiaojunQAQ
RepositorySkillJect
Skill nameeeat-content-quality-audit
Stars
79
Forks
8
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by jiaxiaojunQAQ on GitHub. Read the source before you install it.

Installation

Install the Eeat Content Quality Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/jiaxiaojunQAQ/SkillJect.git /tmp/SkillJect
mkdir -p .claude/skills
cp -r /tmp/SkillJect/data/skills_sample/eeat-content-quality-audit-1.0.0 .claude/skills/eeat-content-quality-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Eeat Content Quality Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Eeat Content Quality Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Eeat Content Quality Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

EEAT Content Quality Audit

This skill is developed based on the CORE-EEAT Content Benchmark, providing 80 standardized content quality audit criteria.

Skill Overview

This skill evaluates content quality through 80 standardized criteria across 8 core dimensions. It generates comprehensive audit reports including item-level scores, dimension scores, system scores (GEO/SEO), content-type weighted total scores, veto item detection, and priority action plans.

Applicable Scenarios

Use this skill when users request the following:

  • Content quality check or audit
  • EEAT scoring or E-E-A-T audit
  • Content quality assessment
  • CORE-EEAT audit
  • GEO quality scoring
  • Content improvement recommendations
  • AI citation potential assessment
  • Content optimization plan
  • "How good is my content"
  • "Can my content be cited by AI"

Core Capabilities

This skill can:

  1. Complete 80-Item Audit: Score each CORE-EEAT item as Pass/Partial/Fail
  2. Dimension Scoring: Calculate scores for all 8 dimensions (0-100 points each)
  3. System Scoring: Calculate GEO score (CORE) and SEO score (EEAT)
  4. Weighted Total Score: Calculate final score based on content-type specific weights
  5. Veto Item Detection: Flag critical credibility violations (T04, C01, R10)
  6. Priority Ranking: Identify top 5 improvement recommendations by impact
  7. Action Plan: Generate specific, actionable improvement steps

Content Types

This skill supports the following content types, each with different dimension weights:

  • Product Review
  • How-To Guide
  • Comparison Review
  • Landing Page
  • Blog Post
  • FAQ
  • Alternative Recommendation
  • Best Recommendation
  • User Review

Usage

Basic Audit

Please audit the quality of the following content: [Content text or URL]
Perform content quality audit on [URL]

Specify Content Type

Audit this content as a product review: [Content]
Score this tutorial based on 80 criteria: [Content]

Comparison Audit

Audit the differences between my content and competitor's: [Your content] vs [Competitor content]

Data Input Requirements

Manual Data Input (Currently recommended):

Request users to provide:

  1. Content text, URL, or file path
  2. Content type (if cannot auto-detect): Product Review, How-To Guide, Comparison Review, Landing Page, Blog Post, FAQ, Alternative Recommendation, Best Recommendation, User Review
  3. Optional: Competitor content for comparative assessment

Note: Explicitly mark in the output which items cannot be fully evaluated due to lack of access (e.g., backlink data, Schema markup, site-level signals).

Execution Steps

When users request content quality audit, follow these steps:

Step 1: Audit Preparation

markdown
### Audit Preparation

**Content**: [Title or URL]
**Content Type**: [Auto-detected or user-specified]
**Dimension Weights**: [Load from content type weight table]

#### Veto Item Check (Emergency Brake)

| Veto Item | Status | Action |
|-----------|--------|--------|
| T04: Disclosure Statement | ✅ Pass / ⚠️ Triggered | [If triggered: "Immediately add disclosure banner at top of page"] |
| C01: Intent Alignment | ✅ Pass / ⚠️ Triggered | [If triggered: "Rewrite title and first paragraph"] |
| R10: Content Consistency | ✅ Pass / ⚠️ Triggered | [If triggered: "Verify all data before publication"] |

If any veto item is triggered, prominently mark it at the top of the report and recommend immediate action before continuing with the full audit.

Step 2: CORE Audit (40 Items)

Evaluate each item according to standards in references/core-eeat-benchmark.md.

Score each item:

  • Pass = 10 points (Fully meets standard)
  • Partial = 5 points (Partially meets standard)
  • Fail = 0 points (Does not meet standard)
markdown
### 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 Dimension Score**: [X]/100

Evaluate O (Organization), R (Referenceability), and E (Exclusivity) in the same table format, 10 items per dimension.

Step 3: EEAT Audit (40 Items)

markdown
### Exp — Experience

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

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

Evaluate Ept (Expertise), A (Authority), and T (Trust) in the same table format, 10 items per dimension.

For detailed 80-item ID lookup table and site-level item handling instructions, see references/item-reference.md.

Step 4: Scoring and Reporting

Calculate scores and generate final report:

markdown
## 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 Item Status**: ✅ No triggers / ⚠️ [Item] triggered

### Dimension Scores

| Dimension | Score | Rating | Weight | Weighted Score |
|-----------|-------|--------|--------|----------------|
| C — Contextual Clarity | [X]/100 | [Rating] | [X]% | [X] |
| O — Organization | [X]/100 | [Rating] | [X]% | [X] |
| R — Referenceability | [X]/100 | [Rating] | [X]% | [X] |
| E — Exclusivity | [X]/100 | [Rating] | [X]% | [X] |
| Exp — Experience | [X]/100 | [Rating] | [X]% | [X] |
| Ept — Expertise | [X]/100 | [Rating] | [X]% | [X] |
| A — Authority | [X]/100 | [Rating] | [X]% | [X] |
| T — Trust | [X]/100 | [Rating] | [X]% | [X] |
| **Weighted Total Score** | | | | **[X]/100** |

**Score Calculation Formulas**:
- GEO Score = (C + O + R + E) / 4
- SEO Score = (Exp + Ept + A + T) / 4
- Weighted Score = Σ (Dimension Score × Content Type Weight)

**Rating Standards**: 90-100 Excellent | 75-89 Good | 60-74 Fair | 40-59 Poor | 0-39 Very Poor

### Unavailable Item Handling

When an item cannot be evaluated (e.g., A01 backlink profile requires site-level data, inaccessible):

1. Mark the item as "N/A" and note the reason
2. Exclude N/A items from dimension score calculation
3. Dimension Score = (Sum of scored items) / (Number of scored items × 10) × 100
4. If a dimension has >50% items as N/A, mark that dimension as "Insufficient Data" and exclude from weighted total score
5. Recalculate weighted total score using only dimensions with sufficient data, renormalizing weights to total 100%

**Example**: Authority dimension has 8 N/A items and 2 scored items (A05=8, A07=5):
- Dimension Score = (8+5) / (2 × 10) × 100 = 65
- But 8/10 items are N/A (>50%), so mark as "Insufficient Data -- Authority"
- Exclude A dimension from weighted total; redistribute its weight proportionally to remaining dimensions

### Item-Level Scores

#### CORE — Content Body (40 Items)

| ID | Check Item | Score | Notes |
|----|------------|-------|-------|
| C01 | Intent Alignment | [Pass/Partial/Fail] | [Observation] |
| C02 | Direct Answer | [Pass/Partial/Fail] | [Observation] |
| ... | ... | ... | ... |

#### EEAT — Source Credibility (40 Items)

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

### Top 5 Priority Improvements

Sorted by: Weight × Points Lost (by impact from high to low)

1. **[ID] [Name]** — [Specific improvement suggestion]
   - Current Status: [Fail/Partial] | Potential Gain: [X] weighted points
   - Action: [Specific steps]

2. **[ID] [Name]** — [Specific improvement suggestion]
   - Current Status: [Fail/Partial] | Potential Gain: [X] weighted points
   - Action: [Specific steps]

3–5. [Same format]

### Action Plan

#### Quick Wins (Less than 30 minutes each)
- [ ] [Action 1]
- [ ] [Action 2]

#### Medium Investment (1-2 hours)
- [ ] [Action 3]
- [ ] [Action 4]

#### Strategic (Requires Planning)
- [ ] [Action 5]
- [ ] [Action 6]

### Recommended Next Steps

- Complete content rewrite: Rewrite with CORE-EEAT constraints
- GEO optimization: Optimize for failed GEO-First items
- Content refresh: Focus on weak dimensions
- Technical fixes: Check site-level issues

Validation Checkpoints

Input Validation

  • Content source identified (text, URL, or file path)
  • Content type confirmed (auto-detected or user-specified)
  • Content sufficient for meaningful audit (≥300 words)
  • If comparative audit, competitor content also provided

Output Validation

  • All 80 items scored (or marked N/A with reason)
  • All 8 dimension scores calculated correctly
  • Weighted total score matches content type weight configuration
  • Veto items checked and marked if triggered
  • Top 5 improvements sorted by weighted impact, not arbitrary order
  • Each recommendation specific and actionable (not generic)
  • Action plan includes specific steps and investment estimates

Success Points

  1. Start with Veto Items — T04, C01, R10 are one-vote veto items; they affect overall evaluation regardless of total score

  2. Focus on High-Weight Dimensions — Different content types prioritize different dimensions

  3. GEO-First Items are Critical for AI Visibility — If goal is AI citation, prioritize items marked with GEO 🎯

  4. Some EEAT Items Require Site-Level Data — Don't penalize content for things only observable at site level (backlinks, brand recognition)

  5. Use Weighted Scores, Not Just Raw Averages — Product reviews with strong exclusivity are more important than strong authority

  6. Re-Audit After Improvements — Run again to verify score improvements and catch regressions

Terminology

CORE (Content Quality)

  • C (Contextual Clarity): Contextual Clarity — Whether content is clear, accurate, and directly answers user questions
  • O (Organization): Organization — Whether content has good structure, hierarchy, and navigation
  • R (Referenceability): Referenceability — Whether content has sufficient data, evidence, and citations
  • E (Exclusivity): Exclusivity — Whether content offers unique insights, data, and perspectives

EEAT (Source Credibility)

  • Exp (Experience): Experience — Whether author demonstrates actual usage experience
  • Ept (Expertise): Expertise — Whether author demonstrates professional knowledge and skills
  • A (Authority): Authority — Whether content source possesses authority and industry status
  • T (Trust): Trust — Whether content is trustworthy

GEO (Generative Engine Optimization)

  • Content optimization for AI search engines (e.g., Google SGE, Bing Chat)
  • Emphasizes direct answer capability, referenceability, and exclusivity

Reference Documents

  • references/core-eeat-benchmark.md — Complete 80-item benchmark with dimension definitions, scoring standards, and GEO-First item markers
  • references/item-reference.md — Compact lookup table for all 80 item IDs + site-level item handling instructions + sample scored report

Notes

  • Read reference documents only when needed to maintain context conciseness
  • When operations are fragile or require strong consistency, prioritize script execution with result validation
  • Fully leverage the agent's language understanding and generation capabilities; avoid writing scripts for simple tasks
  • This skill primarily serves Chinese users but retains industry terminology (CORE, EEAT, GEO) for alignment with international standards

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Eeat Content Quality Audit AI skill do?

Systematic content quality audit based on 80 CORE-EEAT standards, evaluating content's GEO (Generative Engine Optimization) and SEO (Search Engine Optimization) potential. Features 8-dimension scoring, weighted total calculation, veto item detection, and priority improvement recommendations. Applicable for pre-publication checks, competitive analysis, and AI citation potential assessment.

Why use Eeat Content Quality Audit on TypingMind?

Because you install it once and use it with any model. Eeat Content Quality Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Eeat Content Quality Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jiaxiaojunQAQ/SkillJect/tree/main/data/skills_sample/eeat-content-quality-audit-1.0.0. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Eeat Content Quality Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Eeat Content Quality Audit?

As many as you like. As long as a model supports skills, you can use Eeat Content Quality Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Eeat Content Quality Audit AI skill free?

It is published on GitHub by jiaxiaojunQAQ. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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