seo-score

SkillSearch

Compute the two never-blended 0-100 scores (Search SEO and AI Visibility / GEO-AEO) from a set of findings, with severity-weighted category values, dynamic re-normalization of conditional modules, severity gating, and letter bands. Used by seo-orchestrator and the `score` command.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the seo-score skill

What this skill tells your AI

The instructions your AI receives, as published by hainrixz/claude-seo-ai in skills/seo-score/SKILL.md and read by ahel’s review.

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": [ ... ] } }

Signals

GitHub stars
59
Forks
5
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
seo-score
Source
github.com/hainrixz/claude-seo-ai