Histolab

What it does

When your agent uses it

• Random/grid/score-based tile extraction
• H&E stain normalization
• Tile dataset preparation

Example prompts

• “Use the histolab skill to extract and preprocesses whole-slide histology image tiles with Histolab”
• “/histolab”

Requirements

• Python 3
• Compatibility (from SKILL.md): Requires Python 3.8–3.11 and histolab 0.7.0 on Linux or macOS, plus native OpenSlide. Python 3.10 avoids scikit-image 0.19 source builds on macOS ARM. Optional pooch downloads samples; matplotlib plots results; large-image plus a tile source enables MPP extraction.

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

1. 1Inspect slide.dimensions, slide.levels (a list), and
2. 2Select physical field of view and pixel resolution; level numbers are not
3. 3Choose TissueMask for all tissue sections or BiggestTissueBoxMask for the
4. 4Configure a tiler and preview with the same mask passed to extraction.
5. 5Extract into a distinct per-slide/per-strategy directory. Count saved files,
6. 6Split datasets by patient before training/validation/test tile assignment.

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv
  • brew
  • python

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • arxiv.org
  • github.com
  • openslide.org
  • doi.org
  • export.arxiv.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Requires Python 3.8–3.11 and histolab 0.7.0 on Linux or macOS, plus native OpenSlide. Python 3.10 avoids scikit-image 0.19 source builds on macOS ARM. Optional pooch downloads samples; matplotlib plots results; large-image plus a tile source enables MPP extraction.

  From compatibility in the SKILL.md frontmatter.

Context cost

Histolab loads about 2.2k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 73 tokens; SKILL.md has 884 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~73

When it runs · the whole SKILL.md, loaded when a task matches

~2.2k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~12k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its Apache-2.0 licence (© K-Dense-AI). 884 words, ~2,197 tokens.

name

histolab

description

Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset preparation. For multiplexed imaging or deep learning inference pipelines, use pathml.

compatibility

Requires Python 3.8–3.11 and histolab 0.7.0 on Linux or macOS, plus native OpenSlide. Python 3.10 avoids scikit-image 0.19 source builds on macOS ARM. Optional pooch downloads samples; matplotlib plots results; large-image plus a tile source enables MPP extraction.

license

Apache-2.0 license

metadata.version

1.5

metadata.skill-author

K-Dense Inc.

metadata.last-reviewed

2026-10-01

metadata.upstream-version

0.7.0

uv venv --python 3.10 .venv-histolab
uv pip install --python .venv-histolab/bin/python 'histolab==0.7.0' pooch matplotlib
.venv-histolab/bin/python -c 'import openslide; print(openslide.__library_version__)'

env DYLD_FALLBACK_LIBRARY_PATH="$(brew --prefix openslide)/lib" .venv-histolab/bin/python -c 'import openslide; print(openslide.__library_version__)'

from pathlib import Path
from histolab.slide import Slide
from histolab.masks import TissueMask
from histolab.tiler import RandomTiler

output = Path("output/random_tiles")
output.mkdir(parents=True, exist_ok=True)
slide = Slide("slide.svs", processed_path=output)
mask = TissueMask()
slide.locate_mask(mask).save(output / "mask_preview.png")

tiler = RandomTiler(
    tile_size=(512, 512), n_tiles=100, level=0, seed=42,
    check_tissue=True, tissue_percent=80.0, prefix="random_",
)
tiler.locate_tiles(slide, extraction_mask=mask).save(output / "tile_preview.png")
tiler.extract(slide, extraction_mask=mask)
print("[OK] Saved tiles:", len(list(output.glob("random_tile_*.png"))))

© K-Dense-AI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in skills/histolab of K-Dense-AI/scientific-agent-skills.

• SKILL.md
• references/core_capabilities.md
• references/filters_preprocessing.md
• references/slide_management.md
• references/tile_extraction.md
• references/tissue_masks.md
• references/typical_workflows.md
• references/visualization.md

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

• lingxling/awesome-skills-cnclaude-scientific-skills/skills/histolab