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seo-score

seo-score

github.com/hainrixzMarketing & growth79201 installsUpdated 4d ago
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About seo-score

A skill that calculates Search SEO and AI Visibility scores from findings, applying defined weights, severity caps, bands, and coverage rules. It is for producing reproducible scores from audit results.

Key features

  1. 01Calculates Search SEO and AI scores
  2. 02Applies status and severity factors
  3. 03Adjusts active category weights
  4. 04Caps scores for severe failures
  5. 05Reports bands and coverage

Use cases

  1. 01Scoring a set of SEO findings
  2. 02Comparing search and AI visibility results
  3. 03Producing reproducible audit scores for CI

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hainrixz/claude-seo-ai --skill seo-score

After installing, type/seo-scorein Claude Code to confirm it loaded.

Details

From the project README

seo-score

Turns findings (conforming to schema/finding.schema.json) into the two scores. Full model in references/scoring-model.md — follow it exactly.

Steps

  1. Group findings by the category each module maps to, per score. A finding contributes only to the score(s) in expected_impact.axis (search, ai, or both).
  2. Category value = 100 × Σ(status_factor × severity for scored findings) / Σ(severity), where status_factor: pass 1.0, warn 0.5, fail 0.0. Exclude needs_api and not_applicable from both sums.
  3. Active weights: drop conditional categories (e-commerce/local/international) whose modules produced no findings; re-normalize remaining weights to sum to their active total.
  4. Score = Σ(category_value × weight) / Σ(active weight) for each of Search SEO and AI Visibility.
  5. Severity gating: if any finding has severity: 5 and status: fail, cap the affected score at 40 and set capped: true.
  6. Assign bands (A≥90, B≥80, C≥70, D≥60, F<60) and a one-line interpretation from the Search×AI quadrant. 6b. Coverage floor: report coverage (the % of the axis's always-on weight that carried a scored finding). Below 50% the axis comes back provisional: true with state: "partial" — quote the band and the coverage figure together, never the letter on its own.
  7. M21 (AI discovery & agent endpoints — llms.txt, agents.md, UCP, agentic sitemap) weight is 0 — report it, never let it move the AI score.

Determinism

Prefer node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --run <run-dir> (it reads <run-dir>/findings.json) or --findings <path> for a bare findings file, adding --vertical a,b, --multilingual and --environment production|preview|staging|local when the file carries no run context, so the number is reproducible and CI-checkable. --run takes a path, never the word latest: the score command resolves latest[:host] from <root>/<host>/latest.json first and passes the directory. If Node is unavailable, compute by hand following the same formula and note the fallback. Either way the math must match references/scoring-model.md.

Output

{ "search_seo": { "value": 78, "band": "C", "capped": false, "interpretation": "...", "categories": [ {"name":"Indexability & Crawl","weight":22,"value":91,"active":true}, ... ] },
  "ai_visibility": { "value": 64, "band": "D", "capped": false, "interpretation": "Citable structure missing; add answer blocks and schema.", "categories": [ ... ] } }

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