Full Seo Audit

Full SEO Audit

Run the individual SEO audit skills, then merge their findings into one consolidated, prioritized report. This skill is the orchestrator; the real work is done by the per-area skills it coordinates.

When to use this skill

Use this when the user wants the whole picture rather than one area:

• "Run a full / complete / comprehensive SEO audit of example.com"
• "Do a technical SEO review of my site"
• "Give me one report covering everything that's wrong with my SEO"

For a single area ("check my sitemap", "audit my titles"), use that area's skill directly instead.

Inputs to collect

1. Site URL — the live site root (e.g., https://example.com).
2. Scope — how many pages to crawl (default ~200) and how many sitemap URLs

to probe. Larger sites should be sampled.

1. Focus — run everything (default), or a chosen subset (e.g., "just

crawlability and indexation"). Map the user's intent to the skills below.

1. API key (optional) — Core Web Vitals field data needs a Google PageSpeed

Insights key; without it, that audit uses lab proxies only.

Coverage map

Each row is a separate skill. Run the ones in scope.

| Area | Skill | Crawls / fetches | |---|---|---| | Indexation: sitemaps | sitemap-audit | XML sitemaps | | Crawlability: robots.txt | robots-txt-audit | robots.txt | | Crawlability: architecture | site-architecture-audit | site + robots + sitemap | | Redirects | redirect-audit | URL list / crawl | | Internal links | internal-link-audit | crawl | | External links | external-link-audit | crawl | | Canonical tags | canonical-tag-audit | crawl | | Pagination | pagination-audit | crawl | | Soft 404s | soft-404-audit | crawl | | Titles & descriptions | meta-data-audit | crawl | | Headings | heading-structure-audit | crawl | | Images | image-seo-audit | crawl | | Structured data | schema-markup-audit | crawl | | Social metadata | open-graph-audit | crawl | | Content quality | content-quality-audit | crawl | | Keyword cannibalization | keyword-cannibalization-audit | crawl | | HTTPS / mixed content | mixed-content-audit | crawl | | Page experience | core-web-vitals-audit | per-URL | | AI discoverability | llms-txt-audit | /llms.txt |

Workflow

Step 1: Crawl once into a shared page cache

The page-based audits all read the same HTML, so crawl the site a single time with the shared fetch stage and let every extractor read from that cache:

mkdir -p audits
python3 scripts/fetch_pages.py https://example.com --max-pages 200 --output audits/page_cache.json

Step 2: Extract + audit each in-scope area

For each page-based area in scope, run its extractor with --from-cache (pure, no extra crawl) then its audit script. Save each audit output to the shared folder using a stable, skill-named filename so they can be merged:

# repeat per in-scope page-based skill — all read the ONE page_cache.json
python3 ../meta-data-audit/scripts/extract_metadata.py --from-cache audits/page_cache.json --output audits/meta.inventory.json
python3 ../meta-data-audit/scripts/audit_metadata.py audits/meta.inventory.json --output audits/meta-data-audit.audit_report.json

python3 ../heading-structure-audit/scripts/extract_headings.py --from-cache audits/page_cache.json --output audits/head.inventory.json
python3 ../heading-structure-audit/scripts/audit_headings.py audits/head.inventory.json --output audits/heading-structure-audit.audit_report.json

The skills that read --from-cache are: meta-data, heading-structure, image-seo, schema-markup, open-graph, content-quality, keyword-cannibalization, mixed-content, canonical-tag, pagination, soft-404, and external-link. (A few also run a small secondary probe — canonical targets, share images, the soft-404 missing-page probe — on top of the cached crawl.)

The non-page audits fetch their own thing and don't use the page cache: run them per their own SKILL.md — sitemap-audit, robots-txt-audit, llms-txt-audit, redirect-audit, core-web-vitals-audit, plus internal-link-audit and site-architecture-audit (which crawl with depth tracking of their own).

Step 3: Consolidate

Merge every *.audit_report.json into one cross-skill view:

python3 scripts/consolidate_reports.py --dir audits --output consolidated_report.json

The consolidator emits total issues by severity, a per-skill breakdown, and a flat list of every failing check ranked by severity then count.

Step 4: Produce the consolidated report

Write the report following references/report-template.md:

1. Executive summary — overall health, issue counts by severity, the 3–5

highest-impact fixes across all areas.

1. Scorecard — one row per audited area with its issue counts and a status.
2. Findings by area — a short section per skill summarizing its top issues

and linking to (or inlining) that skill's own detailed report.

1. Prioritized roadmap — a single cross-area action list ordered by impact,

not by area.

Step 5: Prioritize across areas

Rank fixes by impact, not by which skill found them. Apply this order:

1. Indexation blockers first — anything stopping pages from being crawled or

indexed (robots Disallow: /, sitewide noindex, sitemap full of dead URLs, broken canonicals) outranks on-page polish.

1. Sitewide/template issues over one-off issues — a bug in one template

affecting 500 pages beats a single page's long title.

1. High-traffic, high-intent pages first within a given fix.
2. Group related findings across skills (e.g., the same http→https migration

surfaces in sitemap, redirect, internal-link, canonical, and mixed-content audits — present it once as a single root-cause fix).

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/report-template.md — consolidated report structure
• references/coverage-map.md — what each sub-skill covers and what it needs
• scripts/consolidate_reports.py — merge per-skill audit reports into one ranked report

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.