PAL | Twitter Card Checker for Social Previews avatar

PAL | Twitter Card Checker for Social Previews

Pricing

from $4.00 / 1,000 completed social card audits

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PAL | Twitter Card Checker for Social Previews

PAL | Twitter Card Checker for Social Previews

Twitter Card checker for public HTML pages. Audit twitter:card, title, description and image metadata, flag missing or incomplete social preview tags, and export CSV/JSON. Does not render a live X preview image.

Pricing

from $4.00 / 1,000 completed social card audits

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Practical AI Lab

Practical AI Lab

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1

Monthly active users

17 hours ago

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My Actor 17

Check X/Twitter card metadata before sharing campaign links

Designed for: Social media managers and web developers troubleshooting missing link preview metadata.

What you receive: Per-page checks of published Twitter/X card metadata with missing-field flags for export and correction.

Test one real page in under a minute

Paste this into the Input tab and press Start:

{"urls":["https://scrapeme.live/shop/Pikachu/"]}

Enter a landing page, run, inspect the tags, and re-run after a page update. Compare with the PAL Open Graph checker for related preview metadata.

Billing: Pay per event for processed pages; confirm the exact amount in this Actor’s Pricing tab before a run. Export Dataset results as JSON or CSV and rerun after editing your site.

Limitations: This reads static HTML tags only; it cannot predict how X will render or cache a card. Only public static HTML; no account login, JavaScript rendering or edits to third-party websites.

Continue your workflow with PAL


PAL Social Card Audit

Detect Twitter/X summary card tags and missing required preview data.

Ideal users and practical workflow

Best for: SEO specialists, store owners and content teams.

What it checks: Detect Twitter/X summary card tags and missing required preview data. Upload a short list of public HTTPS URLs to receive an individual evidence-based record and issue flags per page. Review the flagged URLs first, then export the Dataset as JSON or CSV for your team's workflow.

When it is useful: Before releasing a new page, after a redesign, or during a monthly search-indexing review.

What it does not do: It does not crawl an entire website automatically, render JavaScript, guarantee a search ranking, or change the target site. Check the exact limitations below before purchasing runs.

Why use this PAL Actor?

Get a structured, repeatable report for this specific issue without opening dozens of webpages by hand. Each input URL is analyzed independently. The output identifies data found on the page and flags likely omissions for manual review. Save output in Apify Dataset and export to JSON, CSV or Excel.

Practical use cases

Built for: SEO specialists, technical site auditors, ecommerce growth teams.

  • Spot the issue: Detect Twitter/X summary card tags and missing required preview data. See machine-readable results for each submitted public URL.
  • Prioritize corrections: use issues, issueCount and details to decide which pages merit human review.
  • Repeat as needed: rerun the same URL list after editing page markup to compare findings.

What makes this tool useful?

Focused on Social Card Audit, rather than requiring a full-site crawling subscription. Export results to a spreadsheet, CSV or a data pipeline; connect via Apify API where appropriate. The tool processes static HTML and embedded metadata, with no client-side browser, API keys or private-page logins.

Important: each URL is a separate charged successful audit event at the rate visible in Apify Store. A missing signal is an observation, not a legal or search-engine verdict. If your site renders important data only with JavaScript, that data may not appear in the result.

How this fits with other Practical AI Lab (PAL) tools

For ecommerce projects, start with PAL Product Price & Stock Snapshot and follow with PAL Product GTIN & SKU SEO Auditor to inspect identifiers. For storefront trust information, use PAL Store Policy Link Mapper before reviewing return or shipping schema. These are independent PAL tools; there is no bundle requirement.

Example input

{"urls": ["https://scrapeme.live/shop/Pikachu/"]}

Results

Each successful fetch produces a Dataset row with sourceUrl, finalUrl, mode, issueCount, issues and details. Issue flags indicate markup detected in static HTML; they are not a guarantee of legal compliance, accessibility certification, search rank, or a live inventory position. Missing data can be published through JavaScript or other channels not read here.

Billing

Pay per event: pal-twitter is triggered for each successfully fetched and audited page at the price displayed by Apify Store. URL errors generate a free error row. Maximum 18 URLs per run. No paid API keys, logins, or third-party services required.

Technical limits

Public HTTPS only; no JavaScript rendering, captcha bypass or private pages. Each response is at most 1.5 MB, 11-second network timeout. The site may block bots. Output reflects visible HTML at retrieval time, not a complete website audit. Running the Actor does not itself fix issues.

More Practical AI Lab (PAL) tools

Use independent PAL tools in a natural sequence: first capture price and stock, then audit the corresponding product markup; or locate policy links and inspect returns/shipping markup. Each Actor is separately usable, with no mandatory bundle.

Browse the PAL developer profile for additional focused audit tools.


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