seo-score skill by hainrixz

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

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).
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.
Active weights: drop conditional categories (e-commerce/local/international) whose modules produced no findings; re-normalize remaining weights to sum to their active total.
Score = Σ(category_value × weight) / Σ(active weight) for each of Search SEO and AI Visibility.
Severity gating: if any finding has severity: 5 and status: fail, cap the affected score at 40 and set capped: true.
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.
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

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

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).

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.

Active weights: drop conditional categories (e-commerce/local/international) whose modules produced no findings; re-normalize remaining weights to sum to their active total.

Score = Σ(category_value × weight) / Σ(active weight) for each of Search SEO and AI Visibility.

Severity gating: if any finding has severity: 5 and status: fail, cap the affected score at 40 and set capped: true.

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.

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

Output

{ "search_seo": { "value": 78, "band": "C", "capped": false

seo-score

Documentation

Documentation

seo-score

Steps

Determinism

Output

Documentation

seo-score

Documentation

seo-score

Steps

Determinism

Output