Serp Trust Auditor

SERP-TRUST Auditor

Executive Summary

The SERP-TRUST framework is a 50-item proprietary scoring system that measures how much Google trusts a domain to appear and rank in competitive search results. Trust is distinct from authority — a site can have high Domain Rating (authority) but low SERP trust due to thin content, missing schema, poor CWV, or inconsistent NAP signals. In 2025–2026, SERP trust has a direct AI visibility component: Google's AI Overviews and third-party LLMs (ChatGPT, Perplexity) apply their own trust filters before citing sources. Sites scoring <50 on SERP-TRUST are rarely cited in AI answers regardless of organic ranking. The framework evaluates 5 dimensions: Technical Foundation (T), Ranking Signals (R), User Experience (U), Search Authority (S), and Trust & AI Readiness (A) — 10 items × 4-point scale per dimension = 200 raw points, normalized to 0–100.

2025 SERP-TRUST benchmarks:

• Overall score ≥80: competitive (citeable by AI Overviews); ≥90: market leader
• Technical Foundation: HTTPS enforced, INP <200ms (replaced FID March 2024), no crawl errors
• Ranking Signals: pillar pages with Surfer Score ≥80, FAQPage schema on all service pages
• User Experience: Core Web Vitals all "Good" (LCP <2.5s, INP <200ms, CLS <0.1)
• Search Authority: Domain Rating ≥30 for local; TF:CF ratio ≥0.5; branded anchor 50–60%
• Trust & AI Readiness: Organization schema + sameAs on homepage; GBP verified; 5+ review platforms
• Veto rule: any single Critical failure (e.g., active manual action, no HTTPS, score = 0 on T dimension) caps total score at ≤40 regardless of other dimensions

Numbered Action Plan:

Immediate (Week 1, High Impact/Low Effort)

1. Validate all Technical Foundation items — run python3 scripts/check_url.py --url [URL] --full for HTTPS, redirect chain, TTFB. Run Lighthouse → record LCP, INP, CLS scores. Effort: 30 min. Priority: 25.
2. Check for critical veto triggers — active manual actions (GSC), HTTP accessible URL, 4xx/5xx homepage, no HTTPS = automatic score cap. Effort: 10 min.
3. Score all 50 items — work through each dimension in order (T→R→U→S→A), applying 0–4 scale. Note evidence for every score ≠ 4. Effort: 1–2 hrs. Use python3 scripts/score_calculator.py --st to compute.
4. Identify veto check failures — each dimension has a veto check that caps the dimension score. Flag any failures immediately as Critical blockers. Effort: 15 min.
5. Generate competitor comparison — score at least 2 top competitors on the same 50 items (abbreviated: focus on T and A dimensions). Gap = priority list. Effort: 45 min/competitor.

Short-Term (Week 2–4)

6. Fix all T dimension failures first — Technical Foundation is the prerequisite layer; fixing T items produces the highest dimension ROI. Target: T dimension score ≥8/10 (80%) before moving to other dimensions. Effort: varies.
7. Add missing structured data — Organization schema (homepage), LocalBusiness subtype (homepage), FAQPage (all service pages), HowTo (process pages). Effort: 2–4 hrs.
8. Improve UX dimension — fix largest CWV failures first: LCP (often image optimization or render-blocking resources), INP (event listener optimization), CLS (reserve space for images/embeds). Effort: 4–8 hrs dev.
9. Build Trust & AI Readiness — verify GBP, claim all sameAs properties, add review widget with AggregateRating schema, add author bylines with Person schema. Effort: 2–4 hrs.
10. Write SERP-TRUST findings to {AUDIT_DIR}/serp-trust-scores.md — YAML frontmatter + full 50-item scorecard + Priority Matrix + competitor comparison. Run python3 scripts/score_calculator.py --st to generate final score. Effort: 1 hr.

Output files:

• {AUDIT_DIR}/serp-trust-scores.md — 50-item scorecard with scores and evidence
• {REPORTS_DIR}/serp-trust-score.pdf — auto-generated PDF via python3 scripts/generate_pdf.py

Prerequisites

Before scoring, confirm you have:

• Website URL (must be accessible — run python3 scripts/check_url.py --url [URL] --full)
• Target keywords (minimum 5 — from {AUDIT_DIR}/keyword-gaps.md or {AUDIT_DIR}/intake-data.md)
• At least 3 competitor URLs (from {AUDIT_DIR}/competitor-profiles.md)
• Target location(s) for local context

If any are missing, collect them before proceeding.

Tools for this phase:

2025 SERP-TRUST Context:

• INP replaced FID as Core Web Vital (March 2024) — target <200ms (Good: <100ms)
• AI Overviews (AIO) appear for 20–35% of local queries — T2 dimension captures this
• Schema completeness is both a Technical (T) AND Trust (T2) signal in 2025
• FAQPage schema = primary AIO citation trigger — assess in both T and T2
• Helpful Content System folded into core algorithm March 2024 — content quality now a direct ranking signal in R dimension

Framework Reference

Load the complete scoring rubric from references/serp-trust-benchmark.md.

Framework: SERP-TRUST (Search Engine Results Page — Technical Reliability, User Signals & Search Trust) Items: 50 | Scale: 0–4 per item | Max Raw: 200 | Normalized: 0–100

Scoring Dimensions

Execution Process

Step 1: Research Phase (30–45 min)

Gather evidence for each dimension BEFORE scoring:

T — Technical Foundation

1. Fetch [domain]/robots.txt — check for blocks and sitemap declaration
2. Fetch /sitemap.xml — validate exists, has correct URLs, accurate lastmod
3. Check SSL: curl -I https://[domain] — verify HTTPS, HSTS header
4. Run Google Rich Results Test on homepage + 2 service pages — count schema types
5. GSC URL Inspection → "Test Live URL" → View Rendered HTML (JS rendering check)
6. Screaming Frog crawl → canonical tags, redirect chains, orphan pages

R — Ranking Signals

1. GSC Performance → top 20 queries — check CTR vs. benchmark (target >3% for branded)
2. Ahrefs → Organic Keywords — list top 10 ranking pages and their primary keywords
3. Manual check title + H1 alignment on each top-5 pages
4. Screaming Frog → Content → word count per page type (service ≥800, blog ≥1,200)
5. Surfer SEO side-by-side vs. top competitor on 2 key service pages

U — User Experience & Performance

1. PageSpeed Insights → Mobile: record LCP, INP, CLS, TTFB scores for homepage
2. PageSpeed Insights → Mobile: record same for top service page
3. Lighthouse → Accessibility score (target ≥90)
4. Mobile viewport test at 375px — horizontal scroll? tap targets ≥44px?
5. Microsoft Clarity or Hotjar: any rage-click or dead-click patterns? (if access)

S — Search Authority

1. Ahrefs → Domain Rating (DR) vs. competitors — note gap
2. Ahrefs → Referring Domains count + % from niche-relevant sites
3. Majestic → Trust Flow / Citation Flow ratio (TF:CF target ≥0.5)
4. Ahrefs → Anchor text profile — flag if exact-match commercial anchors >15%
5. Ahrefs → Organic Traffic trend (6 months) — stable/growing or declining?

T2 — Trust & AI Readiness

1. Search [business name] → Knowledge Panel present? Complete?
2. Search best [service] in [city] → AIO appears? Client cited?
3. Ask ChatGPT: "Who are the best [service] providers in [city]?" — client mentioned?
4. Ask Perplexity: "Best [service] in [city]" — client cited?
5. GSC → Reviews report + check aggregate rating schema on homepage
6. sameAs schema count (target ≥7 authoritative properties)

Step 2: Score Each Item (0–4 Scale)

For each of the 50 items, assign a score using the rubric from references/serp-trust-benchmark.md:

Record evidence string for each score: e.g., "T1: HTTPS + HSTS present — curl confirms 301 from HTTP [Score: 4]"

2025-specific scoring notes:

• INP (not FID): score INP target <100ms = 4, 100–200ms = 3, 200–500ms = 2, >500ms = 0–1
• FAQPage schema: score 4 if present on all service pages, 3 if homepage only, 2 if one page, 0 if missing
• AIO citation: score 4 if cited in 3+ AIO queries, 3 if 1–2, 2 if AIO appears but not cited, 0 if AIO doesn't even appear
• Knowledge Panel: score 4 if full panel + claimed, 3 if partial, 2 if only GBP card, 0 if nothing

Step 3: Veto Check

Check all 7 veto conditions — triggered vetoes cap the maximum final score:

Step 4: Calculate Final Score

Raw Score = Sum of all 50 item scores (max 200)
Normalized = (Raw Score / 200) × 100
Final Score = min(Normalized, lowest triggered veto cap)

Optional dimension-weighted scoring (recommended for granular analysis):

Weighted = (T_pct × 0.20) + (R_pct × 0.25) + (U_pct × 0.20) + (S_pct × 0.20) + (T2_pct × 0.15)

Score interpretation:

Step 5: Score Competitors (Abbreviated)

For each of 3 competitors, score on key items per dimension (abbreviated — focus on observable signals):

Step 6: Priority Quick Wins

For all items scored 0–1, calculate improvement priority:

Output Format

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 SERP-TRUST SCORECARD
 Website: [URL]
 Date: [Date]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

 OVERALL SCORE: [X] / 100    Grade: [A-F]

 Dimension Breakdown:
 T  Technical Foundation   [XX/40]  ████████░░  [X%]
 R  Ranking Signals        [XX/40]  ███████░░░  [X%]
 U  User Experience        [XX/40]  █████░░░░░  [X%]
 S  Search Authority       [XX/40]  ████████░░  [X%]
 T2 Trust & AI Readiness   [XX/40]  ██████░░░░  [X%]

 Veto Checks:
 [✅/❌] V01: Site Indexed (site:[domain] returns pages)
 [✅/❌] V02: No Manual Penalty (GSC clear)
 [✅/❌] V03: HTTPS Active + SSL valid
 [✅/❌] V04: LCP < 6s on mobile
 [✅/❌] V05: No Cloaking detected
 [✅/❌] V06: Toxic Links < 50%
 [✅/❌] V07: Has Structured Data (schema present)

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 COMPETITOR COMPARISON
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 | Metric     | Client | Comp 1 | Comp 2 | Comp 3 |
 |------------|--------|--------|--------|--------|
 | Overall    |   XX   |   XX   |   XX   |   XX   |
 | Technical  |   XX%  |   XX%  |   XX%  |   XX%  |
 | Ranking    |   XX%  |   XX%  |   XX%  |   XX%  |
 | UX/Perf    |   XX%  |   XX%  |   XX%  |   XX%  |
 | Authority  |   XX%  |   XX%  |   XX%  |   XX%  |
 | AI Ready   |   XX%  |   XX%  |   XX%  |   XX%  |

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 TOP 5 IMPROVEMENT PRIORITIES
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 1. [Item ID]: [Description] — Current: X/4 → Target: 4/4 — Impact: High — Effort: [X]
 2. [Item ID]: [Description] — Current: X/4 → Target: 3/4 — Impact: High — Effort: [X]
 3. [Item ID]: [Description] — Current: X/4 → Target: 4/4 — Impact: Med — Effort: [X]
 4. [Item ID]: [Description] — Current: X/4 → Target: 3/4 — Impact: Med — Effort: [X]
 5. [Item ID]: [Description] — Current: X/4 → Target: 3/4 — Impact: Med — Effort: [X]

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 QUICK WINS (Score to 3–4 with <1hr effort)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 • [Item]: [What to do] — Effort: [time] — Expected gain: +X points (+X/100)
 • [Item]: [What to do] — Effort: [time] — Expected gain: +X points (+X/100)
 • [Item]: [What to do] — Effort: [time] — Expected gain: +X points (+X/100)

SEO Health Index (Combined Score)

If LOCAL-IMPACT has also been scored, compute the combined index:

SEO Health Index = (LOCAL-IMPACT Score × 0.55) + (SERP-TRUST Score × 0.45)

Report as the master metric in the final output.

Handoff

Save results to {AUDIT_DIR}/serp-trust-scores.md with YAML data block:

---
skill: cross-cutting/serp-trust-auditor
phase: scoring
date: [YYYY-MM-DD]
business: [Business Name]
url: [URL]
framework: SERP-TRUST
version: 1.0
scores:
  overall: [0-100]
  grade: [A-F]
  weighted: [0-100]
  dimensions:
    T: { raw: X, max: 40, pct: X }
    R: { raw: X, max: 40, pct: X }
    U: { raw: X, max: 40, pct: X }
    S: { raw: X, max: 40, pct: X }
    T2: { raw: X, max: 40, pct: X }
  vetoes_triggered: [list veto codes or empty]
  competitors:
    - name: [comp1]
      url: [url]
      score: X
    - name: [comp2]
      url: [url]
      score: X
  seo_health_index: [0-100]
---

Key consumers:

• output/report-generation — SERP-TRUST score integrates into master report
• output/pdf-report — renders score dashboard with dimension bar chart in PDF
• cross-cutting/local-impact-auditor — combines for SEO Health Index composite score