Heading Structure Audit

Heading Structure Audit

Audit the heading hierarchy (H1–H6) of a website and produce an actionable SEO and accessibility report.

When to use this skill

Use this skill when the user asks to:

• Audit or analyze the heading tags or heading hierarchy of a website
• Find pages with missing, empty, or multiple H1s
• Find broken outlines: skipped heading levels (e.g., H2 jumping to H4) or pages that don't start at H1
• Identify overly long or duplicated headings
• Improve content structure, document outline, or accessibility of headings

Inputs to collect

Before starting, confirm with the user:

1. Site URL or local files — a live site root URL (e.g., https://example.com), a sitemap URL, a list of URLs, or a local folder of HTML files.
2. Scope — full site, a specific section (e.g., /blog/), or a list of URLs.
3. Crawl limits — max pages (default 500) for live crawls.
4. Long-heading threshold — character count above which a heading is "too long" (default 70).

Workflow

Step 1: Gather the page set and extract headings

• If a sitemap is available (/sitemap.xml), it is used to get the canonical page list.
• Otherwise, the crawler starts from the homepage following only same-host links.
• For local HTML folders, all .html files are enumerated.

Use scripts/extract_headings.py to build a heading inventory:

python3 scripts/extract_headings.py https://example.com --max-pages 500 --output heading_inventory.json
# already crawled once (e.g. in a full SEO audit)? skip the crawl and reuse the shared cache:
# python3 scripts/fetch_pages.py https://example.com --output page_cache.json
# python3 scripts/extract_headings.py --from-cache page_cache.json --output heading_inventory.json

For every page the inventory records the <title> and the full list of headings in document order, each with its level (1–6) and trimmed text.

Step 2: Run the audit checks

Use scripts/audit_headings.py to run all audit checks against the inventory:

python3 scripts/audit_headings.py heading_inventory.json --long-heading 70 --output audit_report.json

Step 3: Evaluate the audit checks

Evaluate each check defined in references/audit-checks.md. The core checks are:

Step 4: Produce the report

Write a report following the structure in references/report-template.md:

1. Summary — pages crawled, headings found, issue counts by severity
2. Issues — one section per failing check, listing the page, the offending heading(s), and a specific fix
3. Prioritized action list — ordered by severity and estimated impact

Step 5: Recommend fixes

For each issue, give a concrete, copy-pasteable recommendation. When proposing headings:

• Every page should have exactly one H1 that states the page's primary topic
• Headings should form a logical, gap-free outline: H1 → H2 → H3, never skipping a level downward
• Base every suggested heading on the page's actual content; never invent topics the page does not cover
• Reserve heading tags for true section titles — do not wrap styling-only text in headings, and do not demote real section titles to <div>s for visual reasons (use CSS instead)

Example recommendations:

• Add an H1 to /pricing: H1: Pricing Plans for Teams of Every Size
• /blog/post-1 jumps from H2 to H4 under "Methodology" — change the H4 subsections to H3
• Merge the two H1s on the homepage; demote the tagline H1 to a paragraph and keep the brand-value H1

Optional: export the report

As a Word document (.docx)

If the user wants the report as a .docx (for example, to share with stakeholders or attach to a ticket), save the Markdown report to a file and convert it:

python3 scripts/md_to_docx.py report.md --output report.docx

scripts/md_to_docx.py uses only the Python standard library (no pip install) and renders headings, tables, lists, links, bold/italic, and code blocks. Offer this whenever a user asks for a Word doc, a .docx, or a shareable/downloadable report.

As a CSV of findings (.csv)

If the user wants the raw findings as a spreadsheet (for filtering, sorting, or triage in Sheets or Excel), convert the audit's audit_report.json directly:

python3 scripts/findings_to_csv.py audit_report.json --output findings.csv

scripts/findings_to_csv.py is also standard-library only. It writes one row per finding, with check and severity columns prepended and list fields (e.g. the pages sharing a duplicate value) joined with ; . Unlike the .docx, which reformats the written report, the CSV is a direct dump of the structured findings — offer it whenever a user wants the data itself, a spreadsheet, or to slice findings by check or severity.

Resources

• scripts/md_to_docx.py — convert the Markdown report into a Word (.docx) document (standard library only)
• scripts/findings_to_csv.py — flatten the audit findings JSON into a CSV, one row per finding (standard library only)
• references/audit-checks.md — full definitions, thresholds, and rationale for every audit check
• references/report-template.md — report output structure
• scripts/extract_headings.py — crawl a site and build the heading inventory
• scripts/audit_headings.py — run audit checks against a heading inventory JSON file