No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by Oldcircle · Codex Skill · ★ 225
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is geo-sleuth safe to install? View the security audit →
🧭 geo-sleuth An agent skill that finds where a photo was taken — and shows its work. Works with <a href="https://
| Stars | 225 |
| Forks | 24 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 69.2192680070615/100 |
| Last Updated | 2026-09-21 |
| Created | 2026-09-18 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~17k |
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geo-sleuth is An agent skill that finds where a photo was taken — OpenStreetMap geometry, elevation skylines, satellite imagery and street view — and shows its work. Works with Claude Code, Codex, Cursor, Gemini CL. It is categorized as a Codex Skill with 225 GitHub stars.
geo-sleuth is primarily written in Python. It covers topics such as agent-skills, ai-agents, claude-code.
You can find installation instructions and usage details in the geo-sleuth GitHub repository at github.com/Oldcircle/geo-sleuth. The project has 225 stars and 24 forks, indicating an active community.
geo-sleuth is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to geo-sleuth on Agent Skills Hub include agent-skills, awesome-ai-agent-skills, memorix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: