model-selection SKILL.md skillA
model-selection 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/model-selection@git:20261002.0400856Pins git:20261002.0400856 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/model-selection/SKILL.md- Versions recorded
- 4
- Latest version
- git:20261002.0400856, committed Oct 2, 2026
- First version recorded
- Sep 30, 2026
- Size
- 10,715 bytes
- Repository stars
- 346
- License
- MIT
Use when choosing the model for a medical-imaging study. Picks a paper-grounded architecture family (CNN/ViT, U-Net/nnU-Net, detection, SAM/foundation, GNN), then vets the concrete repo or checkpoint for licence, version pin, weight provenance and benchmark overlap.
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
# Model-Selection Skill Two questions, in this order. Phases 1–3 answer a literature question with a stable answer: which architecture **family** suits the task. Phases 4–6 answer a provenance question: which concrete **artifact** — repository, revision, checkpoint — will be run, and what its numbers may claim. The skill writes decision notes and runs one stdlib gate; it never downloads, runs, trains or benchmarks a model, and it describes archetypes, not a live SOTA leaderboard. Elsewhere: building the repo → `/model-scaffold`; profiling data and planning preprocessing → `/imaging-data`; validation design, metrics, uncertainty, explainability → `/model-assessment`; documenting a model you built → `/model-card`; an LLM/MLLM, including benchmark contamination in that setting → `/mllm-eval`; AI-vs-expert reader study → `/design-ai-benchmarking`. ## Workflow ### Phase 1 — Frame the question State the **task** (classification / segmentation / detection / synthesis / transfer), the **modality and dimensionality** (2-D vs 3-D volume), the **labelled-data scale** (events / structures, not just images), **label availability** (lots / few / unlabelled pool), and the …
Read the whole file at its exact version.
How to install
mdr add aperivue/medsci-skills/model-selection@sha256:d800d0379f2bcc5eThe line at the top of this page pins the label git:20261002.0400856, 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_vdjvetnk7jc4mwo6)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Sep 30, 2026 and Oct 2, 2026, more than one a day.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20261002.0400856 latest | 2026-10-02 | 0400856 | 10,715 B | A | view · diff |
| git:20260930.c8ed96c | 2026-09-30 | c8ed96c | 9,690 B | A | view · diff |
| git:20260930.30387c2 | 2026-09-30 | 30387c2 | 9,705 B | A | view · diff |
| git:20260930.e4f475f | 2026-09-30 | e4f475f | 9,771 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 (10715 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 · 346 stars · license MIT · pushed 2026-10-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_vdjvetnk7jc4mwo6 GET https://markdownregistry.com/api/v1/resolve?ref=aperivue/medsci-skills/model-selection GET https://markdownregistry.com/api/v1/blob/d800d0379f2bcc5ee23203e465b20ab7d5c4c2487eb282e0f4b00239acdd97ef
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.
More from aperivue/medsci-skills
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