Internal Link Audit

Internal Link Audit

Audit the internal linking structure of a website and produce an actionable SEO report.

When to use this skill

Use this skill when the user asks to:

• Audit or analyze internal links on a website
• Find broken internal links or redirect chains
• Identify orphan pages (pages with no internal links pointing to them)
• Review anchor text quality for internal links
• Improve crawl depth, site architecture, or internal link equity distribution

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, 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) and max depth (default 5) for live crawls.

Workflow

Step 1: Gather the page set

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

Use scripts/crawl_links.py to crawl a live site and extract all internal links into a JSON link graph:

python3 scripts/crawl_links.py https://example.com --max-pages 500 --max-depth 5 --output link_graph.json

Step 2: Build the link graph

For every page, record:

• Outgoing internal links: target URL, anchor text, rel attributes (nofollow), whether the link is in `/` or in main content
• HTTP status of each target (200, 3xx, 4xx, 5xx)
• Page metadata: title, canonical URL, meta robots (noindex, nofollow)

Step 3: Run the audit checks

Use scripts/analyze_graph.py to analyze the link graph:

python3 scripts/analyze_graph.py link_graph.json --output audit_report.json

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

| Check | Severity | |---|---| | Broken internal links (4xx/5xx targets) | High | | Orphan pages (in sitemap but zero inbound internal links) | High | | Redirect chains and redirected internal links (3xx targets) | Medium | | Deep pages (click depth > 3 from homepage) | Medium | | Generic anchor text ("click here", "read more", bare URLs) | Medium | | Pages with excessive outgoing links (> 150) | Low | | Nofollow on internal links | Low | | Links to non-canonical or noindexed URLs | Medium | | Low inbound link count on important pages | Medium |

Step 4: Produce the report

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

1. Summary — pages crawled, total internal links, issue counts by severity
2. Issues — one section per failing check, listing affected source page, target page, anchor text, and a specific fix
3. Opportunities — pages that deserve more internal links, suggested anchor text using target page keywords
4. Prioritized action list — ordered by severity and estimated impact

Step 5: Recommend fixes

For each issue, give a concrete, copy-pasteable recommendation, e.g.:

• Replace the broken link /old-page on /blog/post-1 with /new-page
• Add 2–3 contextual links to the orphan page /services/seo-audit from topically related pages
• Change anchor text "click here" on /about to descriptive text containing the target page's primary keyword

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/crawl_links.py — crawl a site and build the internal link graph
• scripts/analyze_graph.py — run audit checks against a link graph JSON file

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.