PlaybookPrompts

Generate an hreflang implementation brief for a multi-region site

Marketing & SEO technical-seointernational-seoimplementation

International SEO breaks down at the hreflang step — developers implement it wrong and SEOs struggle to write a brief that leaves nothing ambiguous. This prompt produces a precise implementation spec.

Prompt
You are a technical SEO specialist. I need an hreflang implementation brief for a website with the following setup:

- Regions and languages served: {{REGIONS_AND_LANGUAGES}}
- URL structure used: {{URL_STRUCTURE}} (e.g. subdirectories like /en-gb/, subdomains like gb.site.com, or separate domains)
- CMS or platform: {{CMS_PLATFORM}}

1. Explain in one paragraph what hreflang does and the specific problem it solves for this site — written for a developer who has not worked on international SEO before.
2. Write the exact hreflang tag set for a sample page at {{SAMPLE_PAGE_URL}}, covering all regions listed above. Use correct ISO 639-1 language codes and ISO 3166-1 alpha-2 country codes.
3. List the 4 most common implementation mistakes for the URL structure I'm using, with a broken example and a corrected example for each.
4. Specify where the tags should be placed (HTML head, HTTP header, or XML sitemap) and explain when each method is appropriate.
5. Outline a QA checklist (5–7 checks) a developer can run after implementation to confirm it's working correctly.

Note: If the site serves the same language to multiple regions with no content differences, flag that hreflang may add complexity without clear benefit.
Variables to fill in
  • {{REGIONS_AND_LANGUAGES}}
  • {{URL_STRUCTURE}}
  • {{CMS_PLATFORM}}
  • {{SAMPLE_PAGE_URL}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{REGIONS_AND_LANGUAGES}}{{URL_STRUCTURE}}{{CMS_PLATFORM}}{{SAMPLE_PAGE_URL}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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