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CGIAR Climate Action CDH Skills

Climate Data Hub · AI Tools

CGIAR Climate Data Hub Skills

Standardized, reproducible workflows for climate and agriculture research — driven by plain language, not code.

Get started View on GitHub
  1. 01

    You describe what you need

    “Show me accumulated rainfall for Kenya, March–May 2021, per district.”

  2. 02

    The right skill runs

    Download, spatial processing, or the full pipeline — Claude picks the workflow.

  3. 03

    You get the output

    An interactive dashboard, ready to open.

GCF Pipeline · start here

One request, start to finish

Download, spatial processing, and visualization, chained in one conversation — type a sentence, get an interactive dashboard.

“Show me accumulated precipitation for Kenya for the 2021 long rains season (March–May) at district level.”

Full walkthrough: GCF Pipeline

All skills

7 more, plus the pipeline above
Climate Data Download Acquisition
CHIRPS, CHIRTS-ERA5, AgERA5, and NASA POWER data for any country or bounding box. Python · aggeodata
Soil Data Download Acquisition
SoilGrids soil properties across depth layers, stacked into a validated soil datacube. Python · aggeodata
Geospatial Cube Processor Processing
Clips rasters to admin boundaries, stacks sources, exports zonal stats as a tidy CSV. Python · xarray
Spatial Crop Modeler Modeling
Runs DSSAT across climate and soil datacubes for spatially-explicit crop yield maps. Python · ag-cube-cm
Notebook Plots Visualization
Interactive Plotly charts written into a Jupyter notebook, plus a standalone HTML export. Python · Plotly
Climate Dashboard Visualization
Self-contained HTML dashboard — KPI cards, filters, sortable table. No server needed. HTML · Chart.js
CDH Metadata Metadata
Generates a valid CDH YAML metadata record for a dataset — ready for the catalog. YAML