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

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

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).