popv-cell-annotation SKILL.md skillA
popv-cell-annotation 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/popv-cell-annotation@git:20260929.7a7d60fPins git:20260929.7a7d60f 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/genomics-bioinformatics/single-cell/popv-cell-annotation/SKILL.md- Versions recorded
- 4
- Latest version
- git:20260929.7a7d60f, committed Sep 29, 2026
- First version recorded
- May 28, 2026
- Size
- 27,768 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Consensus cell type annotation: runs 10+ algorithms (KNN-Harmony/BBKNN/Scanorama/scVI, CellTypist, ONCLASS, Random Forest, SCANVI, SVM, XGBoost) on a labeled reference and transfers labels via majority voting. Outputs per-method labels, consensus, agreement score. Use when single-method annotation is insufficient or you need ensemble uncertainty for novel states.
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
# popV Multi-Method Cell Type Transfer ## Overview popV (Population Voting for single-cell annotation) annotates a query scRNA-seq dataset by running 10+ independent classification algorithms against a labeled reference atlas and aggregating results via majority voting. Each method produces its own label; the final `popv_prediction` is the consensus across all methods, and the `popv_agreement` score quantifies how many methods agree. This ensemble strategy is robust to individual method failures on unusual datasets and provides a principled uncertainty estimate: low agreement highlights novel cell states or annotation gaps. ## When to Use - Annotating a query dataset by transferring labels from a well-curated reference atlas when you want a consensus rather than a single model's judgment - Identifying novel or ambiguous cell states as cells where methods disagree (low `popv_agreement` score) - Benchmarking annotation reliability by comparing per-method labels to detect systematic disagreements - Annotating large atlas datasets (>100k cells) where batch effects between reference and query are substantial …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/popv-cell-annotation@sha256:08c971ba460ffe19The line at the top of this page pins the label git:20260929.7a7d60f, 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_tpwvbxdt3pwkmzmr)
2 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between May 28, 2026 and Sep 29, 2026, about one every 41 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260929.7a7d60f latest | 2026-09-29 | 7a7d60f | 27,768 B | A | view · diff |
| git:20260929.35fe6e3 | 2026-09-29 | 35fe6e3 | 27,817 B | A | view · diff |
| git:20260827.cbbeb75 | 2026-08-27 | cbbeb75 | 24,524 B | A | view · diff |
| git:20260528.3e3f998 | 2026-05-28 | 3e3f998 | 24,930 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 (27768 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
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_tpwvbxdt3pwkmzmr GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/popv-cell-annotation GET https://markdownregistry.com/api/v1/blob/08c971ba460ffe19d7a0395178992581b6909796af83ce2b1267b6972df67e41
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.