RRepoGEO

REPOGEO REPORT · LITE

xarray-contrib/xarray-spatial

Default branch main · commit a3e5d772 · scanned 6/6/2026, 6:51:45 AM

GitHub: 948 stars · 94 forks

AI VISIBILITY SCORE
67 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface xarray-contrib/xarray-spatial, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition README to clearly state its purpose as an algorithm library

    Why:

    CURRENT
    The README excerpt starts with `> [!IMPORTANT] **xarray-spatial uses AI assistance...`
    COPY-PASTE FIX
    Add the following sentence at the very top of the README, before any notices or badges: "xarray-spatial is a Python library providing a comprehensive suite of Numba-accelerated spatial analysis algorithms designed to operate natively on xarray DataArray objects for high-performance raster data processing."
  • mediumtopics#2
    Add "algorithms" to the repository topics

    Why:

    CURRENT
    numba, python, raster-analysis, spatial-analysis, xarray
    COPY-PASTE FIX
    numba, python, raster-analysis, spatial-analysis, xarray, algorithms
  • lowreadme#3
    Add an explicit statement about xarray-spatial's core differentiator

    Why:

    COPY-PASTE FIX
    Add a sentence or short paragraph to the README, ideally near the top, stating: "Its core differentiator is providing a comprehensive suite of Numba-accelerated, raster-based spatial analysis functions that operate natively on `xarray.DataArray` objects, leveraging `xarray`'s metadata handling and Dask integration for scalable, high-performance geospatial processing."

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
1 / 2
50% of queries surface xarray-contrib/xarray-spatial
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
7%
Of all named tools, what % are you?
Top rival
Rasterio
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Rasterio · recommended 1×
  2. xarray · recommended 1×
  3. Dask · recommended 1×
  4. NumPy · recommended 1×
  5. SciPy · recommended 1×
  • CATEGORY QUERY
    How to perform efficient spatial analysis on raster data using Python and Numba?
    you: not recommended
    AI recommended (in order):
    1. Rasterio
    2. xarray
    3. Dask
    4. NumPy
    5. SciPy
    6. PyTorch
    7. TensorFlow
    8. OpenCV

    AI recommended 8 alternatives but never named xarray-contrib/xarray-spatial. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Python library for high-performance geospatial data processing with xarray.
    you: #1
    AI recommended (in order):
    1. Xarray-Spatial (makepath/xarray-spatial) ← you
    2. Datashader (holoviz/datashader)
    3. Rasterio (rasterio/rasterio)
    4. Dask-GeoPandas (dask-geopandas/dask-geopandas)
    5. Pyresample (pyresample/pyresample)
    6. rioxarray (corteva/rioxarray)
    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of xarray-contrib/xarray-spatial?
    pass
    AI did not name xarray-contrib/xarray-spatial — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts xarray-contrib/xarray-spatial in production, what risks or prerequisites should they evaluate first?
    pass
    AI named xarray-contrib/xarray-spatial explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo xarray-contrib/xarray-spatial solve, and who is the primary audience?
    pass
    AI named xarray-contrib/xarray-spatial explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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