# geo-scope

> geo-scope — tmolavi-geo-scope. Use this tool when you need to evaluate and compare the performance of multiple AI models on geospatial data, or to conduct reproducible research in the field of geography. The geo-scope framework provides a standardized interface for observing and benchmarking AI models, accepting geospatial datasets as input and producing empirical visibility benchmarks as output. It is ideal for researchers and developers seeking to advance GEO research and improve AI model transparency.

Canonical page: https://skillsregistry.net/skills/tmolavi-geo-scope  
JSON: https://api.skillsregistry.net/v1/skills/tmolavi-geo-scope

## Description

Open framework for empirical AI visibility benchmarks, multi-model provider observation, and reproducible GEO research.

## Trust

- **Trust score (0–1):** 0.73
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/tmolavi/geo-scope)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "tmolavi-geo-scope"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/tmolavi-geo-scope` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/tmolavi-geo-scope/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt