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Semantic site auditor

Skill siddiqss/semantic-seo-suite/skills/semantic-site-auditor

Grounded semantic SEO, GEO & off-page as Claude Code skills — with a fabrication guard that refuses to invent numbers. Free & MIT.

Install
npx -y skills add siddiqss/semantic-seo-suite --skill semantic-site-auditor

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Audit an existing site against its topical map — coverage gaps, keyword cannibalization, entity drift, orphan pages, and per-page micro-semantic issues. Use whenever the user asks to audit a site, find content gaps, check for cannibalization, asks "why aren't we ranking", wants to know what's missing from their niche coverage, or wants a pre-sales content audit of any domain. Produces a prioritised audit report with provenance on every finding. Triggers on audit/gap/cannibalization intent broadly.

SKILL.md

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semantic-site-auditor

Turn a live site + its topical map into a prioritised, evidence-backed fix list. Every finding carries provenance (measured from crawl, derived from embeddings) — no invented scores. This is also the strongest pre-sales artifact for services work: run it on a prospect's domain before a call.

Read first: ../../framework/topical-map-theory.md (gap/section logic), ../../framework/internal-linking-rules.md (orphans), ../../framework/eav-modeling.md (drift = claimed vs perceived identity).

Preconditions

  • brands/<slug>/config.yaml (tier).
  • A topical-map.json to audit against. If none exists, run topical-map-builder first (you can't measure coverage without a target map).
  • entity-profile.json (for the claimed-identity centroid used by drift).

Workflow

  1. Crawl + extract the site into brands/<slug>/data/crawl/:

    python ../../scripts/crawl_sitemap.py --domain <domain> --max-pages 500 --out /tmp/urls.json
python ../../scripts/extract_page_content.py --urls /tmp/urls.json --out-dir brands/<slug>/data/crawl

    Robustness: crawl_sitemap.py falls back to a same-domain BFS when there's no sitemap, respects robots.txt, and caps pages/depth. For JS-rendered sites, extraction may be thin — note that in the report rather than treating missing content as a gap.

  2. Run the analysis engine:

    python ../../scripts/audit_site.py \
  --map brands/<slug>/topical-map.json --crawl-dir brands/<slug>/data/crawl \
  --entity-profile brands/<slug>/entity-profile.json \
  --locked brands/<slug>/locked-facts.json --brand "<Brand>" \
  --out brands/<slug>/audits/<date>-full.md

    It matches each page to its nearest map node (embedding cosine) and reports:

    • Coverage gaps — nodes with no matching page (derived).
    • Cannibalization — page pairs with high similarity + same intent, and any node hit by multiple pages (derived).
    • Entity drift — pages farthest from the core-section centroid, i.e. content pulling the site away from its claimed identity (derived). At T0 (no embeddings), do this qualitatively and label it asserted — never emit a fake distance.
    • Orphans — pages with no incoming internal links (measured from the crawl link graph).
    • Micro-audit — per-page lint (naked stats, fluff, unanswered question headings) reusing the draft rules.

  3. Review + prioritise. The report ends with a prioritised action list: create (gap), consolidate/redirect (cannibalization), rewrite/relink or prune (drift), relink (orphan). Sanity-check each finding — with the offline hash-fallback embeddings, similarities are coarse; re-run with a model backend before making irreversible calls (redirects/prunes).

  4. Feed back into the map. Apply status_updates from the audit JSON (matched nodes → published with their URL); mark thin/drifting matched nodes needs-update; add the confirmed gaps to calendar.md as new priorities.

  5. Render the heatmap (../../scripts/map_heatmap.py) after status updates so coverage is visible at a glance.

Definition of done

  • Report produced with all five finding types, each provenance-tagged.
  • At least one finding is verifiable by hand (a true gap or a true cannibalization pair).
  • Map statuses updated; gaps flowed into the calendar.
  • No fabricated scores anywhere (drift/cannibalization are derived or clearly asserted).

Grounding ladder

  • T0: crawl + extract still work (they're just HTTP); matching/cannibalization/drift are LLM-qualitative and labeled asserted. Orphans + micro-audit are measured.
  • T1: embedding-based matching/cannibalization/drift (derived) — the real version.
  • T1+GSC: confirm cannibalization with pages sharing top queries in Search Console (the strongest, measured signal) — see seo-performance-tracker.

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