claude

eumetsat-skills

EUMETSAT agent skills: eumdac, ewccli, firecube, esf-satellite-data, feature-db-client, ewc-community-hub, ml-menu

32 on GitHubby Armagan Karatosunv0.1.0CC-BY-4.0 AND MITupdated 2 days agodevelopment
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Plugin eumetsat-skills from marketplace eumetsat in eumetsat/skills. Commands read from the repo's manifest — 2 days ago.

What it installs

Skills (7)

  • esf-satellite-data

    Use when building reproducible satellite imagery datasets around detected weather features from the EUMETSAT Earth System Feature database, including feature selection, class balancing, coverage checks, access-route planning, volume estimates, and manifests across EUMETSAT Data Store, EUMETSAT S3 bu

  • eumdac

    Use when the user mentions the `eumdac` CLI or Python package (EUMETSAT Data Access Client), the EUMETSAT Data Store or Data Tailor, collection IDs like `EO:EUM:DAT:...`, or asks to search, list, download or order satellite products (MSG/SEVIRI, MTG), check tokens or credentials, or manage subscript

  • ewc-community-hub

    Use when contributing an item to the EWC Community Hub catalog (ewcloud/ewc-community-hub) — drafting or reviewing items.yaml metadata, annotations, values/inputSpec, running the metadata schema validator, testing a new or EWCCLI-compatible item before submission with a custom-catalogue dry-run, or

  • ewccli

    Use when working with ewccli, the European Weather Cloud command line interface, for EWC setup, login profiles, OpenStack application credentials, Community Hub item discovery/deployment, infrastructure commands, custom catalogues, or CLI troubleshooting.

  • feature-db-client

    Use when interacting with the Earth System Feature Database through the feature_client Python library (FeatureAPIClient, features.apiclient) - fetching or saving features as GeoDataFrames, spatial, temporal and tag queries, nearest-feature search, managing reference data such as satellites, feature

  • firecube

    Use when working with Firecube, the EUMETSAT plugin-based batch ingestion CLI and Python SDK that turns Earth Observation products into analysis-ready datacubes, for installation, running ingestion, developing/testing/packaging plugins, Zarr/Parquet/Tensogram archive operations, chunk control-plane

  • ml-menu

    Works with the EUMETSAT Data Store and eumdac to find Climate Data Records, specifically. The skill is designed to improve data discoverability for long time series for training of ML models, trend analysis, anomaly detection. Covers clouds, albedo, radiation, precipitation, winds, aerosol, ozone, t

View source on GitHub

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