schema-org

name	schema-org
slug	schema-org
displayName	Schema.org Markup Generator
summary	FAQPage / Article / Breadcrumb JSON-LD (no LLM needed)
description	Use when you need Schema.org JSON-LD structured data. Pure Python — no LLM call required. Supports FAQPage, Article, Breadcrumb. Part of brand-loom; hosted brand-memory version at neoxra.com.
version	0.1.0
license	Apache-2.0
compatibility	Claude Code, Cursor, OpenClaw, or standalone via pip install brand-loom
homepage	https://github.com/hogan-tech/brand-loom
when_to_use	schema.org markup, JSON-LD, structured data, SEO rich snippets
argument-hint	<faqs_json> [--schema-type faq]
metadata	{"author":"hogan-tech","discipline":"marketing","hosted":"https://neoxra.com"}

Schema.org Markup Generator

Use when you need Schema.org JSON-LD structured data. Pure Python — no LLM call required. Supports FAQPage, Article, Breadcrumb.

Quick start

• CLI: brand-loom run schema_org --text '[{"q":"What is X?","a":"X is..."}]'
• Chain: brand-loom chain faq,schema_org --text "Our product helps teams..."
• Python:

  from brand_loom.agent import run_skill
  from brand_loom.providers import use_provider
  
  use_provider("openai")  # or "anthropic", "gemini", "ollama", "fake"
  result = run_skill("schema_org", "your topic here")
  print(result.text)
  

Install

pip install brand-loom            # standalone (no coding agent needed)
npx skills add hogan-tech/brand-loom  # via skills.sh

Going further

Want hooks auto-matched to your brand voice, across every platform, no setup? → neoxra.com