histolab-wsi-processing SKILL.md skillA
histolab-wsi-processing from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/histolab-wsi-processing@git:20260528.a140b59Pins git:20260528.a140b59 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/medical-imaging/histolab-wsi-processing/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260528.a140b59, committed May 28, 2026
- Size
- 23,035 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
WSI processing for digital pathology. Tissue detection, tile extraction (random, grid, score-based), filter pipelines for H&E/IHC. For dataset prep, tile-based DL, slide QC. Use pathml for multiplexed imaging.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Histolab WSI Processing ## Overview Histolab is a Python library for processing whole slide images (WSI) in digital pathology. It automates tissue detection, extracts informative tiles from gigapixel images using multiple strategies, and provides composable filter pipelines for preprocessing. The library handles SVS, TIFF, NDPI, and other WSI formats via OpenSlide. ## When to Use - Extracting tiles from whole slide images for deep learning model training - Detecting tissue regions and filtering background/artifacts in histopathology slides - Building preprocessing pipelines for H&E or IHC stained tissue sections - Creating quality-driven tile datasets ranked by nuclei density or cellularity - Performing batch tile extraction across slide collections with consistent parameters - Assessing slide quality and tissue coverage before computational pathology workflows - For raw slide access without tile extraction, use `openslide-python` directly - For complex multiplexed imaging or spatial proteomics pipelines, use `pathml` instead ## Prerequisites - **Python packages**: `histolab` (includes OpenSlide Python bindings) …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/histolab-wsi-processing@sha256:757735dc530add64The line at the top of this page pins the label git:20260528.a140b59, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_hhyzux7vpdmbztjs)
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Versions
The registry has recorded 1 version of this file, committed on May 28, 2026.
Audit of the latest version
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Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_hhyzux7vpdmbztjs GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/histolab-wsi-processing GET https://markdownregistry.com/api/v1/blob/757735dc530add647f94760d8f5713d6cd2fa5b0a36d99ae39cd9f16e052b5ec
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Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.