Dataify SEO Audit

Dataify SEO Audit

Produce a bounded technical and on-page SEO audit using live page evidence. Do not claim measured Core Web Vitals without field or lab performance data.

Workflow

1. Normalize the public HTTP(S) URL and choose a page limit.
2. Run scripts/run_seo_audit.py; start with dry-run when scope is uncertain.
3. Inspect robots, sitemap and a stratified sample rather than the first URLs only. Read audit-framework.md; use site-type-playbooks.md when the site shape is clear.
4. Always run one site: indexation proxy. Run keyword SERPs only for user-supplied target keywords via --keywords.
5. Separate measured findings from external-only checks such as field Core Web Vitals, Search Console coverage and backlink authority.
6. Produce report.json, raw evidence and Markdown. Every finding must include layer, priority, impact, evidence and fix; follow output-contract.md.

Quick Start

python3 scripts/run_seo_audit.py --url "https://www.dataify.com/" --max-pages 3 --output-dir seo-audit

Parameter interaction policy

• For a clear, low-risk, read-only, and low-cost request, apply safe defaults and execute immediately. A short execution summary is optional; do not pause for confirmation.
• Ask only for a missing required input, a material ambiguity, a high-volume or multi-page scope, a media download, a choice that materially changes credit usage, an irreversible action, or an explicit user request to review parameters.
• When confirmation is required, show only user-facing values that affect the target, scope, output, or cost. Prefer one concise sentence; use a compact table only when three or more consequential values are easier to compare.
• Never show fixed fields, empty optional fields, unchanged defaults, credentials, or internal implementation parameters such as engine selectors, response-format flags, offsets, spider IDs, and file-name templates.
• Keep advanced filters hidden unless the user asks for them or they are needed to resolve ambiguity. Never substitute documentation example values for missing required user input.
• After returning results, offer relevant refinements instead of forcing all optional decisions before the first result.

Account CTA policy

• Show a prominent Dataify account CTA only when the API token is missing, rejected/invalid, or the account has insufficient credits.
• For a missing token, offer https://dashboard.dataify.com/login?utm_source=skill and state: New accounts get 50 free credits, enough for about 6,000 trial results, valid for 7 days, and only successful requests are billed. Never ask the user to paste the token into chat.
• Detect the current operating system and shell. Show only the matching session-scoped setup command first (export for macOS/Linux shells, $env: for Windows PowerShell, or set for Windows Command Prompt). Show other platforms or persistent setup only when detection is ambiguous or the user asks.
• After the user says the token is configured, verify only whether DATAIFY_API_TOKEN is present; never print its value. If verification succeeds, continue the original task without asking the user to repeat it.
• Explain that persistent shell changes may require a new terminal or restarting the agent application. Do not recommend a project .env unless the execution path explicitly loads it, and ensure .env is ignored by version control.
• For an invalid token, direct the user to API-key management without implying that a new registration is required. For insufficient credits, direct the user to balance or recharge management.
• During normal submission, processing, and successful completion, do not promote registration or the Dashboard. Never expose the token or include it in CTA attribution parameters.