How to build an SEO audit checklist skill in Claude — and actually act on what it finds.

Google's Agent Development Kit (ADK) formalizes the Claude Skills concept at the framework level. An inline SEO checklist skill is defined in Python with a frontmatter block (name, description, phase, version) and an instructions string that walks the agent through title tag length (50–60 chars, primary keyword near the start), meta description (150–160 chars, CTA included), H2/H3 hierarchy, readability, and schema. The description field is what the LLM reads to decide whether to load the skill — so "SEO optimization checklist for blog posts" is vastly more reliable than "a helpful skill."

The ADK approach shines when SEO audit is one step in a larger pipeline — for example, crawl a URL with one agent, run the SEO checklist skill, then pass the FAIL items to a content rewriting agent. For a standalone site audit, a simpler Claude Project or SKILL.md approach is faster to set up.

Screaming Frog remains the gold standard for site crawls — nothing matches its depth for finding redirect chains, duplicate content, broken canonicals, and missing hreflang tags at scale. The gap is interpretation: a 50-column CSV export with 10,000 rows tells you everything but tells you nothing actionable on its own.

The solution is a two-step chain: export the Screaming Frog CSV, paste the most critical columns (URL, title, meta description, H1, status code, canonical, word count) into Claude with a system prompt that says "score each row PASS/WARN/FAIL, explain each FAIL in one sentence, and rank the top 10 issues by estimated ranking impact." This workflow is documented in detail in the kulbhushanpareek.com Claude Skills guide and is one of the fastest ways to build an SEO audit checklist skill in Claude without writing any code. See also our breakdown of connecting Claude to live marketing data via MCP.

kulbhushanpareek.com's SEO skills library makes an important philosophical point that most skill guides miss: Claude skills replace the analysis, strategy, and content layers of paid SEO tools, not the data-gathering layer. Screaming Frog and Ahrefs provide live crawl data and backlink databases that Claude cannot replicate. But Claude replaces the hours spent interpreting those reports — and this library packages that interpretation layer into eight focused, copy-paste-ready skills.

The Technical SEO Audit skill is the centerpiece: paste a page's HTML or a Screaming Frog CSV, include an optional target keyword and competitor URL, and receive a prioritized PASS/WARN/FAIL action list with one-line fix recommendations for every WARN and FAIL. The library also includes keyword clustering, content gap analysis, and schema generation — eight tools that together could replace a $200+/month subscription stack for a freelancer working at moderate scale.

Writing your own SKILL.md from scratch gives you something no pre-built library can: a checklist that mirrors your exact methodology. The anatomy of a Claude skill is straightforward — YAML frontmatter with name, description, phase, and version; a "When to Use" block; step-by-step instructions; an output format specification; and optionally a reference to a TEMPLATE.md and an EXAMPLE.md with a completed sample. Save the file as seo-audit-checklist.md, place it in .claude/skills/ in your project root, and Claude Code detects it automatically.

Anthropic's own engineering team describes the key design principle: keep the core SKILL.md lean and move detailed reference content (like a full list of schema markup rules) into a separate file that Claude reads only when needed. This prevents context bloat and keeps response times fast. The biggest risk of the DIY path is under-specifying the output format — if you don't define exactly what PASS/WARN/FAIL means and what columns the output table should have, Claude will interpret freely and the output will vary run-to-run.

AdVenture Media's approach represents the far end of the DIY spectrum: using Claude Code to build a complete Node.js SEO crawler from scratch, with axios for HTTP requests and cheerio for HTML parsing. The process starts with a detailed specification — not "build me an SEO audit tool" but a precise brief covering inputs (starting URL, max page limit), what the crawler discovers (internal links, full HTML of each page), and what the analyzer checks (meta patterns specific to your CMS, URL structures your clients use incorrectly, your proprietary weighting system).

Claude Code writes the code, installs dependencies, and fixes syntax errors automatically, narrating each step. The result is a crawler that does exactly what you need — no more, no less — and outputs reports in the template your clients actually read. The trade-off is real: this is a multi-hour project, not a 60-second install. For most teams, one of the pre-built skill libraries above is the faster path. But for large agencies whose value proposition is a proprietary audit methodology, building it in Claude Code instead of hiring a developer is a genuine competitive advantage. Check out our guide on Claude MCP integrations to layer live data onto your custom crawler.