Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Hainrixz/claude-seo-ai/plugin install claude-seo-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-headings-structure)<a href="https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-headings-structure"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/seo-headings-structure/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-headings-structure"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/seo-headings-structure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.01355 |
| Opus 5 | $0.00046 | $0.00678 |
| Sonnet 5 | $0.00018 | $0.00271 |
| Haiku 4.5 | $0.00009 | $0.00136 |
Grade A, and why
seo-headings-structure scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-headings-structure (M7c)
A clean, single-rooted heading tree and proper semantic landmarks make a page's outline machine-readable — the same structure that AI engines use to extract answer blocks and that search engines use to understand content scope. Schema/entity context: references/schema-tier1.md.
Inputs
Work from the PageSnapshot named in your dispatch envelope: read parsed from <run_dir>/pages/<slug>.json (headings[] with region, landmarks); Grep pages/<slug>.html for verbatim evidence; site artifacts live in <run_dir>/site/{robots.json,sitemaps.json,discovery.json}. Deterministic findings already emitted by audit.mjs are listed in <run_dir>/findings.deterministic.json — do not re-emit those ids; add model-judged findings only. If invoked directly with a URL/path and no snapshot exists, first run node "${CLAUDE_PLUGIN_ROOT}/scripts/snapshot.mjs" <target> --out "${CLAUDE_PLUGIN_DATA}/runs" and use the printed snapshot path.
Audits
Working from the PageSnapshot (parsed_rendered when render.used is not none, else parsed):
- Single H1: exactly one
<h1>per page. Zero H1s, or multiple H1s, are both findings. - 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. - 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").
- 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. - 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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago Changed 7a18dd3ef2a7
- 6d ago Changed · +3 lines 19ea9e5ec891
- 13d ago First seen · 44 lines · 91 tokens per session scan A 7613b851d966
seo-headings-structure is a skill published in the GitHub repository Hainrixz/claude-seo-ai (59 stars, last pushed 5d ago), licensed MIT. It adds 91 tokens to every session and 1,355 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
image-seo-audit
Audit every image on a page for SEO, performance, and accessibility — alt text quality, tiered file-size thresholds, WebP/AVIF format adoption, srcset/sizes responsiveness, lazy loading, fetchpriority on the LCP image, and width/height for CLS — producing an optimization list sorted by file-size savings. Triggers on…
design-system
Builds and maintains the design system a product is assembled from — tokens for color, type, spacing and elevation, component contracts, and the rules that keep them coherent as the product grows. Use this when starting a new interface, when screens have drifted apart visually, when the same component exists three…
interface-craft
Raises the visual and interaction quality of an interface — layout, hierarchy, type, spacing, density, and the details that separate a considered product from a generic one. Use this when a screen works but looks unfinished or default, when a layout feels crowded or arbitrary, when a page has no clear focal point, or…
interface-redesign
Upgrades an existing interface to a higher standard without rebuilding it — auditing what is there, identifying what reads as generic or unfinished, and sequencing changes by impact. Use this when a product works but looks dated or default, when a redesign is being considered, when deciding whether to restyle or…
landing-page-audit
Audit a landing page across six conversion dimensions — above-fold clarity, trust signals, form friction, message match against the upstream ad or email, page speed, and mobile experience — each scored 1-10, rolled into an overall score benchmarked against industry averages, with the top 5 fixes ranked by expected…
image-post-processor
After batch completes, runs 4-step post-processing on each image: EXIF strip → WebP convert (q85) → srcset 3 sizes → SEO filename. Generates ImageObject schema fragment. Stage 27e.