geo-sleuth Turns Coding Agents Into Photo Detectives

// 1h agoOPENSOURCE RELEASE

geo-sleuth Turns Coding Agents Into Photo Detectives

geo-sleuth is an open-source Agent Skill that uses OpenStreetMap geometry, elevation data, satellite imagery, and street view to estimate a photo’s camera position and heading—even without readable text or landmarks. It works across Claude Code, Codex, Cursor, Gemini CLI, OpenCode, and GitHub Copilot.

// ANALYSIS

geo-sleuth makes photo geolocation feel less like AI guesswork and more like an auditable search pipeline.

–Scripts rank candidates using geometry, skyline matching, CLIP, DINOv2, and SIFT before the agent makes a final judgment.
–Its showcase cases report meter-scale accuracy, but these are regression tests on previously solved photos—not proof of general-world reliability.
–The evidence-first workflow is valuable for developers building OSINT, mapping, journalism, or visual-reasoning tools.
–Setup is relatively heavy: Python, uv, browser automation, model downloads, and several online imagery services are involved.
–The project’s privacy warning matters because photo geolocation can become invasive when used on images or people without consent. [GitHub repository](https://github.com/Oldcircle/geo-sleuth)

// TAGS

geo-sleuthcoding-agentai-codingvisionsearchopen-sourcedevtool

DISCOVERED

1h ago

2026-11-01

PUBLISHED

1h ago

2026-11-01

RELEVANCE

8/ 10

AUTHOR

GithubProjects

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