Load spatial transcriptomics data from Visium, Xenium, MERFISH, Slide-seq, and other platforms using Squidpy and SpatialData. Read Space Ranger outputs, convert formats, and access spatial coordinates.
SkillScore100Maintained
Automatic
◆Research pack
Last verified 8/2/2026
What it changes
Passed 22 of 22 test cases with the skill, and 18 of 22 without it.
Without skill82%
With skill100%
Checks it passed that the model alone missed
Uses sq.read_visium to load the Space Ranger directory.
Uses sq.read_xenium to import the Xenium output folder.
Identifies expression table attribute as sdata.tables['table'].
and 1 more in the full report
4 fixed18 passed either way0 still failing0 broke
Pass-rate lift
+18 pp
Tokens
+109%
Agent turns
0%
Response time
-41%
Model gemini-3.6-flashMeasured 8/2/2026v122 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 4
Prompt
Write a Python code line using Squidpy to read Slide-seq or Slide-seqV2 bead data from a bead counts CSV file and a spatial coordinates CSV file.
What was checked, without and with the skill
Checked
Without skill
With skill
Calls sq.read_slideseq passing the bead matrix and coordinates_file argument.
Missed
Passed
case-08 · gemini-3.6-flash · 8/2/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md232 linessingle file
Spatial Data I/O
Load and work with spatial transcriptomics data from various platforms.
Required Imports
import squidpy as sq
import scanpy as sc
import anndata as ad
import spatialdata as sd
import spatialdata_io as sdio
Load 10X Visium Data
# Load Space Ranger output (standard method)
adata = sq.read.visium('path/to/spaceranger/output/')
print(f'Loaded {adata.n_obs} spots, {adata.n_vars} genes')
# Spatial coordinates are in adata.obsm['spatial']
print(f"Spatial coords shape: {adata.obsm['spatial'].shape}")
# Image is in adata.uns['spatial']
library_id = list(adata.uns['spatial'].keys())[0]
print(f'Library ID: {library_id}')
Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images. Use when visualizing spatial expression patterns.