single-cell-annotation-guide SKILL.md skillA

single-cell-annotation-guide from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add jaechang-hits/sciagent-skills/single-cell-annotation-guide@git:20260929.7a7d60f

Pins 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/single-cell-annotation-guide/SKILL.md
Versions recorded
3
Latest version
git:20260929.7a7d60f, committed Sep 29, 2026
First version recorded
May 28, 2026
Size
34,356 bytes
Repository stars
381
License
a license file GitHub does not identify

Cell type annotation strategy for scRNA-seq: name clusters manually from canonical markers, transfer labels from a reference (CellTypist, popV), or do both and validate one against the other. Covers matching tissue and developmental stage, marker evidence, annotation confidence, doublets, unresolved clusters. Use when planning or troubleshooting how to annotate cells.

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

# Single-Cell RNA-seq Cell Type Annotation Guide

## Overview

Cell type annotation is the process of assigning biological identities to computationally defined clusters in single-cell RNA-seq data. It is one of the most consequential analytical decisions in a scRNA-seq project: annotation errors propagate into downstream analyses of differential expression, trajectory inference, and cell-cell communication. This guide presents a three-tier decision strategy — manual marker-based annotation first, automated reference-free classification second, and ensemble reference-based label transfer third — and explains when each approach is most appropriate.

The guide synthesizes community know-how on CellTypist (Dominguez Conde et al., Science 2022), popV (Luecken et al., Nature Methods 2024), and classical marker-based approaches, following standards established by the Human Cell Atlas project.
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add jaechang-hits/sciagent-skills/single-cell-annotation-guide@sha256:d34a2cb443313798

The 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_nvl6q5s47og5ci5b.svg)](https://markdownregistry.com/a/art_nvl6q5s47og5ci5b)

2 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 3 versions of this file, between May 28, 2026 and Sep 29, 2026, about one every 62 days.

versioncommittedcommitsizeaudit
git:20260929.7a7d60f latest2026-09-29 7a7d60f 34,356 BA view · diff
git:20260929.35fe6e32026-09-29 35fe6e3 34,398 BA view · diff
git:20260528.3e3f9982026-05-28 3e3f998 31,107 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (34356 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

GitHub

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_nvl6q5s47og5ci5b
GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/single-cell-annotation-guide
GET https://markdownregistry.com/api/v1/blob/d34a2cb443313798c246b1379f82988dc5798c933c23af0df8c0658a729da5da

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.

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