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 agentmods add skills/rebell-leader/spatialai_mcp/spatial-data-validationnpx skills add Rebell-Leader/SpatialAI_MCP --skill spatial-data-validationgit clone --depth 1 https://github.com/Rebell-Leader/SpatialAI_MCPWrote 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/rebell-leader/spatialai_mcp/spatial-data-validation)<a href="https://agentmods.dev/skills/rebell-leader/spatialai_mcp/spatial-data-validation"><img src="https://agentmods.dev/badge/skills/rebell-leader/spatialai_mcp/spatial-data-validation.svg" alt="Measured on agentmods" 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 | $0.00054 | $0.00465 |
| Opus 5 | $0.00027 | $0.00233 |
| Sonnet 5 | $0.00011 | $0.00093 |
| Haiku 4.5 | $0.00005 | $0.00047 |
Grade A, and why
spatial-data-validation 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 6d 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.
What it actually says
Spatial data validation
Validate first, reason second. Never assume a file's format or contents from its extension.
Steps
-
Detect & validate format. Call the MCP tool
validate_spatial_datawith the file path. Choosevalidation_level:basic— extension/existence only.structure(default) — format + structural integrity.integrity— deeper content checks.domain— spatial-biology-specific expectations. For several files, usevalidate_multiple_spatial_files.
-
Read the metadata. Call
analyze_spatial_metadatato extract dimensions, spatial coordinates, and gene/feature info. Confirmobsm['spatial'](AnnData) or coordinate systems (SpatialData) are present when spatial analysis is intended. -
Check raw vs. processed. Integer-valued matrices are likely raw counts; non-integer/log-scaled values are processed. State which the downstream method expects and flag a mismatch.
-
Check compatibility when combining files:
check_spatial_data_compatibility(coordinate systems + gene overlap).
Key facts (see context/data-formats.md)
- A
.zarrstore is SpatialData only if it has SpatialData markers or ≥2 ofimages/ labels/ points/ shapes/ tables/. Otherwise it's a plain zarr array. - iST datasets can be terabytes. Default to lightweight structural checks; avoid
loading whole objects. The heavy scientific stack (
pip install -e ".[spatial]") is optional — the validators degrade gracefully without it.
Don't
- Don't claim a file is valid SpatialData without inspecting contents.
- Don't call execution tools (e.g.
run_nextflow_workflow) — they aren't implemented. Drive local CLIs directly if execution is needed.
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.
- 6d ago First seen · 46 lines · 54 tokens per session scan A 5643a94df974
spatial-data-validation is a skill published in the GitHub repository Rebell-Leader/SpatialAI_MCP (4 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 54 tokens to every session and 465 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
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