AN
Data & Repro
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Data & Repro
SP
spatial-agent
Maintainer FreedomIntelligence · Last updated April 1, 2026
Spatial omics agent: integrate spatial data with imaging, protein, and genomic layers.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/spatial-agent
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- SpatialAgent focuses on the biological interpretation of spatial transcriptomics data, specifically aiming to propose mechanistic hypotheses about tissue organization and cellular interactions.
- Mechanistic Interpretation: When you have clusters or spatial domains and need to understand why they are organized that way.
- Cell-Cell Interaction: To predict and interpret ligand-receptor interactions in a spatial context.
- Hypothesis Generation: To propose biological mechanisms driving the observed spatial heterogeneity.
- Mechanistic Interpretation: When you have clusters or spatial domains and need to understand why they are organized that way. Cell-Cell Interaction: To predict and interpret ligand-receptor interactions in a spatial context. * Hypothesis Generation: To propose biological mechanisms driving the observed spatial heterogeneity.
Source Doc
Excerpt From SKILL.md
Core Capabilities
- Tissue Organization Analysis: Decodes the structural logic of tissues (e.g., layers, niches).
- Cellular Interaction Prediction: Identifies potential signaling pathways active at domain boundaries.
- Hypothesis Proposal: Generates testable biological hypotheses based on spatial data.
Workflow
- Input Analysis: Accepts processed ST data (e.g., cluster annotations, DEG lists per spatial domain).
- Knowledge Retrieval: Queries biological knowledge bases regarding the observed cell types and genes.
- Synthesis: Constructs a narrative explaining the spatial arrangement (e.g., "The proximity of fibroblasts and tumor cells suggests a desmoplastic reaction mediated by TGF-beta signaling...").
Example Usage
User: "Why are the macrophages located at the boundary of the tumor core in this sample?"
Agent Action:
- Analyzes the gene expression of macrophages and adjacent tumor cells.
- Checks for ligand-receptor pairs (e.g., CSF1-CSF1R).
- Proposes: "Macrophages are likely recruited by CSF1 secreted by the tumor cells, forming an immunosuppressive barrier..."
Use cases
- **Mechanistic Interpretation**: When you have clusters or spatial domains and need to understand *why* they are organi.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
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