imaging-data SKILL.md skillA
imaging-data from aperivue/medsci-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add aperivue/medsci-skills/imaging-data@git:20261003.87332eaPins git:20261003.87332ea in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- aperivue/medsci-skills
- Path
skills/imaging-data/SKILL.md- Versions recorded
- 6
- Latest version
- git:20261003.87332ea, committed Oct 3, 2026
- First version recorded
- Sep 30, 2026
- Size
- 11,723 bytes
- Repository stars
- 366
- License
- MIT
Use when preparing a medical-imaging dataset (DICOM/NIfTI) for modelling. Profiles spacing, orientation, intensity, label integrity, foreground fraction and target volume, gates them against the plan, then plans and audits preprocessing and augmentation for leakage.
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
# Imaging-Data Skill
The dataset decides more of a study than the architecture does, and it decides it first. Phases 1–3
establish what the data is and what it will not support, while that is still cheap; Phases 4–7 design
and audit the preparation pipeline so it is leakage-safe before `/model-scaffold` builds the repo.
Describe-and-audit only: never modify, resample, reorient, split or write image data, never run
preprocessing on real patient data, and wire MONAI / TorchIO transforms by reference rather than
writing a new normalisation or resampling implementation.
Elsewhere: tabular/clinical variables → `/generate-codebook`, `/clean-data`; auditing the split
table, held-out metrics, calibration, subgroup results → `/model-assessment`; choosing an
architecture → `/model-selection`; building the repo → `/model-scaffold`.
## Workflow
### Phase 1 — Profile every case
```bash
python3 ${CLAUDE_SKILL_DIR}/scripts/profile_imaging_dataset.py \
--split train:imagesTr:labelsTr \
--split test:imagesTs \
--dataset "MSD Task09 Spleen" \
--declared-labels 0=background,1=spleen \
--target-label 1 \
--plan resample=true,reorient=false,loss=dice_ce,metrics=dice+hd95 \
…Read the whole file at its exact version.
How to install
mdr add aperivue/medsci-skills/imaging-data@sha256:d24f5a9301699da3The line at the top of this page pins the label git:20261003.87332ea, 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_p4ev3akqh52meez5)
1 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 6 versions of this file, between Sep 30, 2026 and Oct 3, 2026, more than one a day.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261003.87332ea latest | 2026-10-03 | 87332ea | 11,723 B | A | view · diff |
| git:20261003.291346d | 2026-10-03 | 291346d | 11,267 B | A | view · diff |
| git:20261002.50c4f8f | 2026-10-02 | 50c4f8f | 11,253 B | A | view · diff |
| git:20260930.c8ed96c | 2026-09-30 | c8ed96c | 11,054 B | A | view · diff |
| git:20260930.30387c2 | 2026-09-30 | 30387c2 | 11,069 B | A | view · diff |
| git:20260930.e4f475f | 2026-09-30 | e4f475f | 11,129 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (11723 bytes)
- pass: No zero-width or bidi control characters
- 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
aperivue/medsci-skills · 366 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_p4ev3akqh52meez5 GET https://markdownregistry.com/api/v1/resolve?ref=aperivue/medsci-skills/imaging-data GET https://markdownregistry.com/api/v1/blob/d24f5a9301699da3f3de76fcc20e324886e9d62812a871d8755a2e0dc985956b
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.