audit
Audit a website or web codebase for SEO and AI-search (GEO/AEO) — produces two independent 0-100 scores (Search SEO + AI Visibility) plus a prioritized,…
Audit and propose fixes for a page's heading hierarchy and semantic outline — verify exactly one H1, logical H2-H6 nesting with no skipped levels, descriptive heading text, and HTML5 landmarks (article/section/nav/main/footer) — so the document outline is extractable. Module
$ npx -y skills add Hainrixz/claude-seo-ai --skill seo-headings-structure --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/seo-headings-structureContext preview
The summary Claude sees to decide when to auto-load this skill.
Audit and propose fixes for a page's heading hierarchy and semantic outline — verify exactly one H1, logical H2-H6 nesting with no skipped levels, descriptive heading text, and HTML5 landmarks (article/section/nav/main/footer) — so the document outline is extractable. Module
name: seo-headings-structure description: Audit and propose fixes for a page's heading hierarchy and semantic outline — verify exactly one H1, logical H2-H6 nesting with no skipped levels, descriptive heading text, and HTML5 landmarks (article/section/nav/main/footer) — so the document outline is extractable. Module M7c. Feeds the Search SEO score (clean headings also support AI answer-block extraction, which is scored separately under M11). allowed-tools: Read, Grep, Glob, WebFetch, Bash
A clean, single-rooted heading tree and proper semantic landmarks make a page's outline machine-readable — the same structure that AI engines use to extract answer blocks and that search engines use to understand content scope. Schema/entity context: `references/schema-tier1.md`.
Work from the PageSnapshot named in your dispatch envelope: read `parsed` from `<run_dir>/pages/<slug>.json` (`headings[]` with `region`, `landmarks`); Grep `pages/<slug>.html` for verbatim evidence; site artifacts live in `<run_dir>/site/{robots.json,sitemaps.json,discovery.json}`. Deterministic findings already emitted by `audit.mjs` are listed in `<run_dir>/findings.deterministic.json` — do not re-emit those ids; add model-judged findings only. If invoked directly with a URL/path and no snapshot exists, first run `node "${CLAUDE_PLUGIN_ROOT}/scripts/snapshot.mjs" <target> --out "${CLAUDE_PLUGIN_DATA}/runs"` and use the printed snapshot path.
Working from the PageSnapshot (`parsed_rendered` when `render.used` is not `none`, else `parsed`): 1. **Single H1**: exactly one `<h1>` per page. Zero H1s, or multiple H1s, are both findings. 2. **No skipped levels**: nesting descends one level at a time (an `<h2>` may be followed by `<h3>`, not directly by `<h4>`). Build the outline and flag any jump. 3. **Descriptive text**: each heading names its section in human terms — flag empty headings, headings used purely for visual styling, and generic placeholders ("Section 1", "Welcome"). 4. **Semantic landmarks**: detect `<main>`, `<article>`, `<section>`, `<nav>`, `<header>`, `<footer>`; flag when headings live inside non-semantic `<div>` soup or when more than one `<main>` exists. 5. **Outline ↔ landmark agreement**: sectioning elements should carry their own heading; orphan landmarks and headings outside any landmark are findings.
Good heading structure feeds AI answer-block extraction: clear H2/H3 boundaries map to candidate quotable passages.
Mark each finding's `fixable` field consistent with `schema/finding.schema.json` (`auto` / `proposed` / `advisory`). Never fabricate a heading's text or invent an H1 from thin content — ask the user or leave a clearly-marked `TODO` placeholder.
Emit findings per `schema/finding.schema.json`. Examples:
Each finding carries `evidence.observed` quoting the page verbatim and a runnable `verification.reproduce`; `expected_impact` is banded + confidence-tagged (no naked percentages).
The SEO + AI-search (GEO/AEO) optimization toolkit for Claude Code — two-score audit + opt-in fixer. Built for 2026-2027.
Repo: Hainrixz/claude-seo-ai
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