cellagent-annotation
SkillAI & modelsUse CellTypeAgent to interpret marker genes, annotate scRNA-seq clusters, and coordinate multi-agent workflows for downstream analysis.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the cellagent-annotation skill
About this skill
The largest open-source medical AI skills library for OpenClaw🦞.
What this skill tells your AI
The instructions your AI receives, as published by freedomintelligence/openclaw-medical-skills in skills/cellagent-annotation/SKILL.md and read by ahel’s review.
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.txtthenpython 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).
Signals
- GitHub stars
- 3k
- Forks
- 412
- Last commit
- Jul 2026
ahel review
K1binfo
installs-packagesK6low
bundled executables the agent is told to runK1binfo
installs-packages (in README.md)
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Item type
- skill
- Key
cellagent-annotation- Source
- github.com/freedomintelligence/openclaw-medical-skills
github.com/freedomintelligence/openclaw-medical-skills
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