How do I install the Cellagent Annotation skill?

Run npx skillmds@latest add biotender-max/cellagent-annotation in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Cellagent Annotation skill do?

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Is Cellagent Annotation safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cellagent Annotation?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cellagent Annotation free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cellagent Annotation?

BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cellagent Annotation by biotender-max

Name: Cellagent Annotation
Author: BioTender-max

File contents

name: cellagent-annotation description: Cell tagger keywords: - single-cell - markers - annotation - confidence - tissue measurable_outcome: Label every provided cluster with a cell type + confidence + marker evidence (or "ambiguous") within 15 minutes per dataset. license: MIT metadata: author: CellAgent Team version: "1.0.0" compatibility: - system: Python 3.9+ allowed-tools: - run_shell_command - read_file

CellAgent Annotation

Use CellTypeAgent to interpret marker genes, annotate scRNA-seq clusters, and coordinate multi-agent workflows for downstream analysis.

When to Use

Automated annotation of scRNA-seq datasets without manual curation.
Multi-step workflows (QC → clustering → annotation → DE analysis).
Integrating multiple batches requiring consistent labeling.

Core Capabilities

Planning: Multi-agent planner decomposes analysis goals into steps.
Tool execution: Generates Scanpy/Seurat code and runs it autonomously.
Self-correction: Detects execution errors and retries with fixes.

Workflow

Gather marker lists per cluster, plus species/tissue context and optional atlas references.
Run CellTypeAgent (pip install -r requirements.txt then python repo/main.py --data data.h5ad --goal annotate).
Review outputs for supporting markers; downgrade ambiguous clusters when signals conflict.
Produce final table (cluster, label, confidence, supporting markers, notes) and cite references when used.

Example Usage

python3 Skills/Genomics/Single_Cell/CellAgent/repo/main.py --data "./data.h5ad" --goal "annotate"

Guardrails

Avoid over-specific lineages if markers overlap; default to broader types.
Flag clusters showing multiple signatures for manual review.
Respect species/tissue differences when interpreting markers.

References

README + upstream paper (Mao et al., 2025 / arXiv 2407.09811).

---name: cellagent-annotationdescription: ---name: cellagent-annotationdescription: Cell taggerkeywords: - single-cell - markers - annotation - confidence - tissuemeasurable_outcome: Label every provided cluster with a cell type + confidence + marker evidence (or "ambiguous") within 15 minutes per dataset.license: MITmetadata: author: CellAgent Team version: "1.0.0"compatibility: - system: Python 3.9+allowed-tools: - run_shell_command - read_file---# CellAgent AnnotationUse CellTypeAgent to interpret marker genes, annotate scRNA-seq clusters, and coordinate multi-agent workflows for downstream analysis.## When to Use- Automated annotation of scRNA-seq datasets without manual curation.- Multi-step workflows (QC → clustering → annotation → DE analysis).- Integrating multiple batches requiring consistent labeling.## Core Capabilities1. **Planning:** Multi-agent planner decomposes analysis goals into steps.2. **Tool execution:** Generates Scanpy/Seurat code and runs it autonomously.3. **Self-correction:** Detects execution errors and retries with fixes.## Workflow1. Gather marker lists per cluster, plus species/tissue context and optional atlas references.2. Run CellTypeAgent (`pip install -r requirements.txt` then `python repo/main.py --data data.h5ad --goal annotate`).3. Review outputs for supporting markers; downgrade ambiguous clusters when signals conflict.4. Produce final table (cluster, label, confidence, supporting markers, notes) and cite references when used.## Example Usage```bashpython3 Skills/Genomics/Single_Cell/CellAgent/repo/main.py --data "./data.h5ad" --goal "annotate"```## Guardrails- Avoid over-specific lineages if markers overlap; default to broader types.- Flag clusters showing multiple signatures for manual review.- Respect species/tissue differences when interpreting markers.## References- README + upstream paper (Mao et al., 2025 / arXiv 2407.09811).

Frequently asked questions

Cellagent Annotation