What we audit, and what we don't
FetchGrade runs a fixed set of deterministic checks across four categories. Every result maps to something we observed on the page — not a model's opinion. Below is exactly what each category measures, how the score is calculated, and the boundaries we keep.
Readable
Visible text, headings, the page title, image descriptions, and content structure — whether key information is real, selectable text rather than locked inside images.
Navigable
Landmarks, link and button names, menu state, keyboard reachability, and whether sampled first-party routes respond.
Actionable
Forms and field labels, required-field clarity, contact paths, the primary call-to-action, and whether overlays block core controls.
Automation friction
JavaScript errors, CAPTCHA or bot challenges, login walls, unsafe redirects, and how quickly the page settles after load.
How the score works
Each category scores (earned ÷ applicable points) × 100. Checks that don't apply to a page are removed from the denominator — never counted as a pass or a fail. The overall score is the sum of each category's contribution, weighted by the percentages above.
- 85–100Strong foundation
- 70–84Good foundation
- 50–69Needs attention
- 0–49Significant friction
What we deliberately don't do
- No free-form clicking, typing, submitting, signing in, buying, or solving CAPTCHAs.
- No whole-domain crawl — we audit one URL plus a small set of public metadata.
- No security, WCAG, SEO, or AI-search ranking claims.
- An LLM only rephrases findings into plain language; it is never the source of truth.