google-earth-engine
Google Earth Engine AI Interface Skill — ee Python API, authentication, image/collection operations, export workflows, GEBCO bathymetry, Sentinel, Landsat
Best use case
google-earth-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Google Earth Engine AI Interface Skill — ee Python API, authentication, image/collection operations, export workflows, GEBCO bathymetry, Sentinel, Landsat
Teams using google-earth-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/google-earth-engine/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How google-earth-engine Compares
| Feature / Agent | google-earth-engine | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Google Earth Engine AI Interface Skill — ee Python API, authentication, image/collection operations, export workflows, GEBCO bathymetry, Sentinel, Landsat
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Google Earth Engine ## When to Use This Skill - Access GEBCO bathymetry, EMODnet seabed, Copernicus marine data - Sentinel-2 / Landsat optical imagery for site characterisation - Time-series analysis (wind speed, SST, wave height) over AOI - Export processed rasters to GeoTIFF for local analysis - Compute statistics over polygon regions (pipeline corridor, lease block) - Interactive map visualisation via geemap in Jupyter notebooks --- ## Sub-Skills - [1.1 Authentication (+2)](11-authentication/SKILL.md) - [2.1 Load and Clip Bathymetry (GEBCO) (+4)](21-load-and-clip-bathymetry-gebco/SKILL.md) - [3.1 Parse getInfo() Results (+2)](31-parse-getinfo-results/SKILL.md) - [4. FAILURE DIAGNOSIS](4-failure-diagnosis/SKILL.md) - [Checklist (+1)](checklist/SKILL.md)
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