AI SEO Audit

Summary

The AI SEO Audit Agent evaluates a page for how readable it is to AI answer engines — ChatGPT, Claude, and Perplexity — rather than classic blue-link search. It fetches the page through context.dev (never touching the site directly), then runs a deterministic rubric of ~30 checks across six categories to a 0–100 total. The model doesn't eyeball the score — audit_page computes it in lib/rules.ts, so the same page always yields the same result. The agent presents the breakdown, lists the failing checks by impact, and returns an agent-ready fix prompt you can paste straight into a coding agent. Reach for it when you want a page to get cited by AI assistants.

Installation

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$ pnpm dlx shadcn@latest add @agentcn/mastra/ai-seo-audit
Copy

Composition

Copy├── config.ts              # Agent definition (model + config)
├── instructions.md        # Audit-and-report instructions
├── tools/
│   └── audit_page.ts      # Runs the deterministic audit, returns the scored result
├── lib/
│   ├── audit.ts           # Fetches via context.dev, parses, and scores the rules
│   ├── rules.ts           # The ~30 checks and six category weights
│   ├── agent-fix-prompt.ts # Builds the copy-paste fix prompts from the findings
│   ├── audit-types.ts     # Shared result types
│   └── url.ts             # URL normalization helpers
└── skills/
    └── seo-audit/
        └── SKILL.md       # How the agent presents the audit_page result

Customization

• Fetching. The page is fetched through context.dev — the recipe never hits the audited site directly. Set CONTEXT_DEV_API_KEY.
• Tune the rubric. Edit lib/rules.ts to add checks, reweight categories, or change the scoring bands — this is the single source of truth for the score.
• Reshape the output. Edit instructions.md or SKILL.md to emit JSON, a shorter summary, or a different fix-prompt format.
• Swap the model. Edit config.ts. The model only narrates the deterministic result, so any capable model works.