Login
Users sign in through the protected login page. API and dashboard routes are guarded until a valid session exists.
Score a webpage against a 47-question E-E-A-T rubric and turn the review into a saved, structured report.
Built for content, SEO, editorial, and quality-review teams, this tool logs users in, tags audits by brand, analyzes a rendered URL, and stores recent runs with an overall score, applicable-question count, and detailed question-by-question explanations.
| ID | Created | URL | Score | Applicable/Total | Brand |
|---|---|---|---|---|---|
| 8 | 2/15/2026 | example-brand.com/.../budgeting-tips | 89% | 44/47 | Example Brand |
| 7 | 2/15/2026 | competitor-3.example/.../cash-back | 86% | 44/47 | Competitor 3 |
| 6 | 12/2/2025 | example-brand.com/.../good-financial-habits | 80% | 45/47 | Example Brand |
Tables scroll horizontally on smaller screens, matching the compact dashboard style.
Instead of manually checking a page against a long E-E-A-T checklist, users submit a URL and receive a structured audit. The tool reviews visible page content, headings, metadata, and rendered content, then scores each rubric question against the expected answer.
It is especially useful for SEO analysts, content strategists, editors, product-content teams, and reviewers who need consistent evidence-based feedback across brands or page types.
E-E-A-T reviews can become inconsistent when every reviewer uses a different checklist or writes feedback in a different format. EEAT Scoring gives teams a shared rubric, a run history, brand filters, overall percentages, and question-level explanations that are easier to compare and act on.
The current app is URL-audit focused: users log in, choose or set a brand, submit a URL, and review saved scoring results.
Users sign in through the protected login page. API and dashboard routes are guarded until a valid session exists.
Tag the run with a brand such as Example Brand, Competitor 1, Example Brand, Example Division, or Competitor 3, then filter history by that brand.
Paste a valid http or https page URL into the dashboard and submit it using the same Score URL flow already in the app.
The server fetches the rendered page, extracts key content signals, and scores each rubric question using the configured model.
The run is saved with score, date, URL, brand, applicable count, and grouped explanations for every rubric item.
These features are based on the current routes, templates, client JavaScript, database structure, and EEAT rubric file.
Scores pages against 47 questions across helpfulness, relevancy, quality, expertise, presentation, page experience, and site-wide signals.
Uses the server-side page fetcher to collect title, canonical, metadata, headings, article/body text, and visible rendered content.
Calculates an overall percentage from applicable questions and stores total versus applicable question counts for each run.
Shows expected answer, model answer, confidence, score, and explanation for each rubric question grouped by area.
Users can set a brand before scoring and filter recent runs so reviews stay organized by client, product line, or content group.
Protected routes require a session. Standard users see their own runs, while admins can see user ownership in the run table.
These are HTML/CSS recreations based on the existing templates and stylesheet. They use realistic demo data from the current dashboard and saved-run format.
A minimal protected entry point with username, password, login status, and the same dark card styling as the app.
After login, users see their identity, logout action, brand controls, URL scoring form, status text, and recent runs table.
| ID | URL | Score | Brand |
|---|---|---|---|
| 8 | example-brand.com/.../budgeting-tips | 89% | Example Brand |
| 7 | competitor-3.example/.../cash-back | 86% | Competitor 3 |
The app’s audit input is intentionally direct: set a brand, enter a URL, and submit Score URL.
During scoring, the dashboard shows the same clear status language used by the current client-side code.
Run details are grouped by rubric area and include expected answer, actual answer, confidence, score, and explanation.
Brand: Example Brand · Overall: 89% — 44/47 applicable questions
The title aligns with the page topic and gives users a clear summary of what the content covers.
No visible byline or reviewer information appears in the extracted page content.
Admin users can see an extra User column in recent runs, helping separate saved audits by account owner.
| ID | Score | Brand | User |
|---|---|---|---|
| 8 | 89% | Example Brand | ahamd |
| 7 | 86% | Competitor 3 | ahamd |
| 6 | 80% | Example Brand | ahamd |
Every run is saved with run metadata and detailed rubric results, making it easier to compare page quality over time and across brands.
Run ID, created date, URL, brand, overall score, total questions, and applicable questions.
Results grouped under Helpfulness, Relevancy, Quality, Expertise, Presentation, Page Experience, and Site-wide sections.
Expected answer, actual answer, score, confidence, and clear Yes, No, or N/A display treatment.
Explanations show why each answer was chosen so users can identify content gaps and improvement opportunities.
The dashboard gives teams a repeatable way to evaluate whether a page is helpful, relevant, high quality, trustworthy, well presented, and technically user-friendly. The saved history and brand filter make it easier to track improvements and compare audits without digging through separate notes or spreadsheets.
Use the links below as placeholders or update them to match your production route/subfolder.