Pagination Audit

Pagination Audit

Audit a website's paginated series and produce an actionable SEO report focused on keeping deep, paginated content indexable.

When to use this skill

Use this skill when the user asks to:

• Audit or fix pagination on blog/category/search listings
• Diagnose why page 2+ of a listing isn't indexed
• Check rel="next" / rel="prev" and canonical handling on paginated pages
• Review infinite-scroll / "load more" SEO

Inputs to collect

1. Site URL or URL list — a live site root to crawl (auto-seeds from

/sitemap.xml), or a text file with --url-list. Include listing pages with their ?page=//page/N/ URLs so the crawler sees the series.

1. Scope — pages to crawl (default 500, --max-pages).

Workflow

Step 1: Crawl and inventory pagination signals

Use scripts/extract_pagination.py:

python3 scripts/extract_pagination.py https://example.com --max-pages 500 --output pagination_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_pagination.py --from-cache page_cache.json --output pagination_inventory.json

It records each page's canonical, meta robots, rel="next"/rel="prev" targets, and the page number detected from the URL (?page=N, /page/N, etc.).

Step 2: Run the audit checks

python3 scripts/audit_pagination.py pagination_inventory.json --output audit_report.json

Step 3: Evaluate the audit checks

Evaluate each check in references/audit-checks.md. Core checks:

| Check | Severity | |---|---| | Paginated page canonicalizes to page 1 | High | | Paginated (page 2+) page is noindexed | Medium | | Paginated page missing a self-canonical | Medium | | Broken rel=next/prev target | Medium | | Inconsistent rel=next/prev reciprocity | Low | | First page carries a redundant ?page=1 | Low | | rel=next/prev present (Google ignores it) | Info |

Step 4: Produce the report

Write a report following references/report-template.md: summary by severity, the canonical-to-page-1 issue first, then indexability and self-canonical gaps, framed as template-level fixes, and a prioritized action list.

Step 5: Recommend fixes

• Canonical to page 1: make each paginated page self-canonical.
• Noindex on page 2+: let component pages be indexable, or guarantee deep

items are reachable (e.g. via the XML sitemap).

• Missing self-canonical: add a self-referencing canonical to every page.
• Broken/inconsistent rel=next/prev: fix the targets or remove them.
• ?page=1 duplicate: serve page 1 at the bare URL and 301 ?page=1 to it.
• Frame fixes at the template level; base everything on observed data.

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 and rationale
• references/report-template.md — report output structure
• scripts/extract_pagination.py — crawl and inventory pagination signals
• scripts/audit_pagination.py — run pagination audit checks

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: JakeLabate
• Source: JakeLabate/Claude-SEO-Skills
• License: MIT
• Homepage: https://www.jakelabate.com/claude-seo-skills/

Install and usage instructions live in the source repository linked above.