Cell tagger
Scanned 9/5/2026
Install to Claude Code
npx -y skills add FridrichMethod/awesome-skills --skill cellagent-annotation --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Cellagent Annotation?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/fridrichmethod-cellagent-annotation)More formats (shields.io, HTML) on the badges page.
---
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
---
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
# 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
1. **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.
## Workflow
1. 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
```bash
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).
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!