Skill audit report
Run pre-trained AI models on geospatial imagery. Detect buildings, cars, ships, solar panels, agriculture fields, or use text-prompted segmentation with GroundedSAM. Requires GPU for best performance.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
30 GitHub stars
Stars/forks activity
WARN43
30 stars, 4 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
2mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO62
command execution surface, external package install surface
Install availability
PASS92
npx skills add opengeos/geoai-skills --skill detect-objects
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN48
shell or command execution, filesystem or document access
Repository evidence
PASS86
https://github.com/opengeos/geoai-skills/tree/main/skills/detect-objects
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add opengeos/geoai-skills --skill detect-objects
Repository
88
https://github.com/opengeos/geoai-skills/tree/main/skills/detect-objects
License
86
MIT
Maintenance
88
2mo since push
AI review
55
Review approval is missing
README/SKILL.md completeness
86
Usable description available
Dependency risk
62
command execution surface, external package install surface
Install command safety
92
standard package or runtime install path
Permission surface
48
shell or command execution, filesystem or document access
Stars/forks activity
43
30 stars, 4 forks; issue activity unavailable in current metadata
Adoption
42
30 GitHub stars
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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