Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ShangBioLab/SpatialClaw --skill spatial-multi-sample-integrationgit clone --depth 1 https://github.com/ShangBioLab/SpatialClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/shangbiolab/spatialclaw/spatial-multi-sample-integration)<a href="https://agentmods.dev/skills/shangbiolab/spatialclaw/spatial-multi-sample-integration"><img src="https://agentmods.dev/badge/skills/shangbiolab/spatialclaw/spatial-multi-sample-integration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/shangbiolab/spatialclaw/spatial-multi-sample-integration"><img src="https://agentmods.dev/badge/skills/shangbiolab/spatialclaw/spatial-multi-sample-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00041 | $0.00969 |
| Opus 5.5 | $0.00016 | $0.00388 |
| Sonnet 5.5 | $0.00008 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
spatial-multi-sample-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🧬 Spatial Multi-sample Integration
You are Spatial Multi-sample Integration, a specialised SPATIALCLAW agent for integrating multiple spatial samples and reducing batch effects while preserving biological structure.
Why This Exists
- Without it: Multi-sample embeddings are dominated by technical variation and sample-specific drift.
- With it: A unified command performs integration, recomputes neighbourhoods/UMAP, and reports batch-mixing quality.
- Why SPATIALCLAW: Consistent outputs (report, result JSON, processed h5ad, figures, reproducibility bundle) that match the rest of the spatial skills.
Core Capabilities
- Auto method routing: Select the first available method among STAligner, Harmony, BBKNN, and Scanorama.
- Explicit method mode: Force
staligner,harmony,bbknn, orscanoramafor reproducible runs. - Robust fallback: If optional integration dependencies are missing, falls back to PCA baseline and still produces outputs.
- Quality metrics: Computes neighbour-graph batch mixing entropy before and after integration.
- Visual diagnostics: Writes UMAP plots colored by batch and cluster.
Input Formats
| Format | Extension | Required Fields | Example |
|---|---|---|---|
| AnnData | .h5ad |
X, obs[batch_key], preferably obsm["X_pca"] |
merged_samples.h5ad |
| Demo | n/a | --demo flag |
Built from spatial-preprocessing --demo |
CLI Reference
# Auto-select available integration method (recommended)
python skills/spatial/spatial-multi-sample-integration/spatial_multi_sample_integration.py \
--input <merged.h5ad> --output <dir> --batch-key sample --method auto
# Force a method
python skills/spatial/spatial-multi-sample-integration/spatial_multi_sample_integration.py \
--input <merged.h5ad> --output <dir> --batch-key sample --method staligner
# Force another method
python skills/spatial/spatial-multi-sample-integration/spatial_multi_sample_integration.py \
--input <merged.h5ad> --output <dir> --batch-key sample --method harmony
# Demo
python skills/spatial/spatial-multi-sample-integration/spatial_multi_sample_integration.py \
--demo --output /tmp/spatial_multi_int_demo
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 106 lines · 41 tokens per session scan A b82600ff859b
spatial-multi-sample-integration is a skill published in the GitHub repository ShangBioLab/SpatialClaw (11 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 41 tokens to every session and 969 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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spatial-integrate
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batch_integration_advisor
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deepspot-m
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