/claude-seo-ai:score

SkillWeb & browsing

Recompute and display the two scores (Search SEO + AI Visibility) from a persisted audit run, without re-crawling. Use to re-show or refresh the scores after an audit, to score a specific run directory or host, or to score a saved findings JSON file.

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 /claude-seo-ai:score skill

What this skill tells your AI

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

Recompute and show the two 0–100 scores by running the seo-score skill, which uses scripts/score.mjs for a reproducible number.

Runs live under <root>/<host>/<run-id>/, where <root> is --out$CLAUDE_SEO_AI_HOME${CLAUDE_PLUGIN_DATA}/runs~/.claude-seo-ai/runs, and <host> is the lower-cased host with :_ (local targets become local/<basename>-<hash>). score.mjs --run takes a directory or a findings file — it does not understand the word latest, so resolve the pointer yourself with Read before you call it: <root>/<host>/latest.json is { run, path, updated_at } and path is the absolute run directory; <root>/index.json lists every host with its latest run id.

  • No argument (default): read <root>/index.json, take the host whose latest run id sorts highest (run ids are UTC YYYY-MM-DDTHH-mm-ssZ, so string order is chronological), read that host's latest.json, then node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --run <path from latest.json>.
  • latest:<host> → read <root>/<host>/latest.json and pass its path to --run.
  • A run directory → node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --run <run-dir> (it reads <run-dir>/findings.json).
  • A findings JSON path → node "${CLAUDE_PLUGIN_ROOT}/scripts/score.mjs" --findings <path> (add --vertical a,b, --multilingual and --environment production|preview|staging|local when the file carries no run context; --manifest <crawl.json> adds the site rollup, --strict exits 2 if any finding fails schema validation, --validate-only reports the per-finding schema verdict without scoring).
  • If no index.json/latest.json exists, or the run has no findings.json, tell the user to run /claude-seo-ai:audit <url> first — never score from memory.

Show both scores with bands, the per-category breakdown, any severity-gating cap (cap_reasons), the unscored state when no category is active, and the needs_api / manual_review / dropped counts. Two scores, never blended. When an axis comes back provisional: true (state: "partial"), say the band and its coverage % in the same sentence — a band built on a third of the model is not the same claim as a measured one, and the per-axis warnings[] name what was not measured. With a rollup, read pages_scored against pages_count: a page listed in unscored_pages[] did not answer 2xx, so it was never scored — name those pages and their status instead of letting the site score stand for a sample that was not measured.

Signals

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