Individual skill
geo-schema
Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup
skills/geo-schema/SKILL.md
Source commit 989cae01e8ebbc42a9ec798eb9e7cb423f5ec89c
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
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Repository context
- Repository stars (not skill ratings)
- 11,615
- Repository last updated
- Nov 10, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- geo Declared skill tag
- schema Declared skill tag
- structured-data Declared skill tag
- json-ld Declared skill tag
- entity-recognition Declared skill tag
- ai-discoverability Declared skill tag
- data Derived category
- security Derived category
Files and excerpt
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# GEO Schema & Structured Data
## Purpose
Structured data is the primary machine-readable signal that tells AI systems what an entity IS, what it does, and how it connects to other entities. While schema markup has traditionally been about earning Google rich results, its role in GEO is fundamentally different: **structured data is how AI models understand and trust your entity**. A complete entity graph in structured data dramatically increases citation probability across all AI search platforms.
## How to Use This Skill
1. Fetch the target page HTML using `fetch_page.py` (see note below)
2. Detect all existing structured data (JSON-LD, Microdata, RDFa)
3. Validate detected schemas against Schema.org specifications
4. Identify missing recommended schemas based on business type
5. Generate ready-to-use JSON-LD code blocks
6. Output GEO-SCHEMA-REPORT.md