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ModernMustardSeedModernMustardSeed/local-growth-crew/skills/local-schema/SKILL.md

local-schema

Skill0 starsChanged 34 days agoMITView on GitHub

Generate and validate LocalBusiness JSON-LD and an llms.txt file for a local business website, from facts the owner confirms. Use when a site needs structured data, an llms.txt, or a fix for schema errors.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Run the AI Search Kit generate_local_business_schema tool with those facts.

    line 11
  2. Very specific:

    Run validate_structured_data on the result and fix every error before you hand it over.

    line 12
  3. Very specific:

    Run generate_llms_txt with the website URL to draft an llms.txt.

    line 13

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Local schema and llms.txt

Business: $ARGUMENTS

  1. Gather the facts: business name, business type, website, phone, email, street address or service area only, city, state, postal code, hours, services, towns served, and profile URLs for sameAs. Ask the owner to confirm any fact you found rather than were given. Never invent one.
  2. Run the AI Search Kit generate_local_business_schema tool with those facts. For a service-area business that does not serve customers at its address, set hide_street_address.
  3. Run validate_structured_data on the result and fix every error before you hand it over.
  4. Run generate_llms_txt with the website URL to draft an llms.txt.
  5. Return both files with install steps: the JSON-LD goes in a <script type="application/ld+json"> tag on the homepage, and llms.txt goes at the site root, served as plain text.

No em dashes.

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