nnunet-segmentation SKILL.md skillA
nnunet-segmentation 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/nnunet-segmentation@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/nnunet-segmentation/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260528.a140b59, committed May 28, 2026
- Size
- 27,388 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Medical image segmentation with nnU-Net's self-configuring framework — auto-selects architecture, preprocessing, training for any modality. CT, MRI, microscopy, ultrasound in 2D, 3D full-res, 3D low-res, cascade. Pipeline: convert → plan/preprocess → train (5-fold CV) → best config → predict → ensemble. Use when classical segmentation fails and annotated data exists.
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
# nnU-Net Automated Medical Image Segmentation ## Overview nnU-Net (no-new-Net) is a self-configuring deep learning framework for biomedical image segmentation. Given a labeled training dataset, nnU-Net automatically determines the optimal network architecture (2D, 3D full-resolution, or 3D cascade), preprocessing steps (resampling, normalization, patch size), training schedule, and post-processing. It consistently achieves state-of-the-art performance across diverse imaging modalities and anatomical structures without manual hyperparameter tuning. nnU-Net v2 (`nnunetv2`) is the current release with a Python API for inference alongside the standard CLI. ## When to Use - Segmenting anatomical structures in CT or MRI scans (organs, tumors, lesions) when you have 20+ annotated training cases - Automating cell or nucleus segmentation in 3D fluorescence or electron microscopy volumes - Establishing a strong baseline for any new segmentation challenge without manually tuning a U-Net - Running inference on new images using a pretrained nnU-Net model from a published challenge - Comparing segmentation methods: nnU-Net's auto-configured ensembles serve as a rigorous baseline …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/nnunet-segmentation@sha256:a19df8259b75722aThe 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_5z6ip5uwdrwd76a7)
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Versions
The registry has recorded 1 version of this file, committed on May 28, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
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- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
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_5z6ip5uwdrwd76a7 GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/nnunet-segmentation GET https://markdownregistry.com/api/v1/blob/a19df8259b75722a72efb2dfb6aa9e2b50593bcf78afd5fe4455cec4de068c5d
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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.