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:
- Complete 80-Item Audit: Score each CORE-EEAT item as Pass/Partial/Fail
- Dimension Scoring: Calculate scores for all 8 dimensions (0-100 points each)
- System Scoring: Calculate GEO score (CORE) and SEO score (EEAT)
- Weighted Total Score: Calculate final score based on content-type specific weights
- Veto Item Detection: Flag critical credibility violations (T04, C01, R10)
- Priority Ranking: Identify top 5 improvement recommendations by impact
- 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:
- Content text, URL, or file path
- Content type (if cannot auto-detect): Product Review, How-To Guide, Comparison Review, Landing Page, Blog Post, FAQ, Alternative Recommendation, Best Recommendation, User Review
- 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
### 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)
### 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)
### 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:
## 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
Output Validation
Success Points
-
Start with Veto Items — T04, C01, R10 are one-vote veto items; they affect overall evaluation regardless of total score
-
Focus on High-Weight Dimensions — Different content types prioritize different dimensions
-
GEO-First Items are Critical for AI Visibility — If goal is AI citation, prioritize items marked with GEO 🎯
-
Some EEAT Items Require Site-Level Data — Don't penalize content for things only observable at site level (backlinks, brand recognition)
-
Use Weighted Scores, Not Just Raw Averages — Product reviews with strong exclusivity are more important than strong authority
-
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