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GeoMaster Geospatial Analysis

Guides an agent through satellite, GIS and spatial analysis workflows with CRS and data-quality checks

Source Download skill
Repository
K-Dense-AI/scientific-agent-skills
Stars
55,780
Licence
MIT
Files
15 files

What it does

Once installed, the agent follows a careful geospatial workflow when you ask about satellite imagery, maps, coordinate systems, terrain or spatial statistics. It checks coordinate reference systems, aligns rasters, preserves nodata and cloud masks, and writes out provenance so results can be checked. It can also use bundled helper code for NDVI, terrain metrics and simple image classification, and it loads only the reference notes relevant to the task.

Great for

  • Remote sensing or GIS analysts who want a checklist-driven assistant that catches CRS and alignment mistakes
  • Students learning Python geospatial workflows with GeoPandas, Rasterio and STAC catalogs
  • Researchers preparing reproducible spatial analyses that need documented provenance

Skip it if

  • Operational decisions such as flood, fire or exposure risk: the skill explicitly says hillshade and demo classifiers are not risk measures, and results need expert validation
  • Projects needing accuracy claims without independent holdout validation: the bundled classifier is a small demonstration model that does not measure accuracy
  • Users with unverified imagery who expect automatic band identification: the helper does not infer bands or masks, so wrong band assumptions can silently produce wrong NDVI

Try asking

  • “Compute NDVI from my masked four-band Sentinel-2 stack and check the CRS and scaling first”
  • “Search the Planetary Computer STAC catalog for low-cloud Sentinel-2 scenes over my study area in June 2023”
  • “Calculate slope and aspect from my metre-based DEM and explain the nodata handling”
  • “Join my point observations to district polygons and summarise counts and means per zone”
Step-by-step guide: how to use GeoMaster Geospatial AnalysisInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 15 original files, the MIT licence and an attribution note.

    geomaster.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip geomaster.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip geomaster.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Give the agent your file paths and metadata (product ID, band order, scale/offset, CRS) up front so it does not have to guess
  • Treat the bundled examples as templates on small known fixtures before running on large or real datasets
  • Ask the agent to report validation design (spatial or temporal holdouts) whenever you report predictive performance

What's inside

  • README.md
  • references/advanced-gis.md
  • references/big-data.md
  • references/code-examples.md
  • references/coordinate-systems.md
  • references/core-libraries.md
  • references/data-sources.md
  • references/gis-software.md
  • references/industry-applications.md
  • references/machine-learning.md
  • references/programming-languages.md
  • references/remote-sensing.md
  • references/review.md
  • references/scientific-domains.md
  • SKILL.md

Redistributed unmodified from K-Dense-AI/scientific-agent-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.