Borrowing it
Nothing to install: this file belongs to cafferychen777/ChatSpatial. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cafferychen777/ChatSpatial/main/.agents/skills/spatial-patterns/SKILL.mdgit clone --depth 1 https://github.com/cafferychen777/ChatSpatialWrote 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/cafferychen777/chatspatial/spatial-patterns)<a href="https://agentmods.dev/skills/cafferychen777/chatspatial/spatial-patterns"><img src="https://agentmods.dev/badge/skills/cafferychen777/chatspatial/spatial-patterns/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/cafferychen777/chatspatial/spatial-patterns"><img src="https://agentmods.dev/badge/skills/cafferychen777/chatspatial/spatial-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.01450 |
| Opus 5.5 | $0.00036 | $0.00580 |
| Sonnet 5.5 | $0.00018 | $0.00290 |
| Haiku 4.5 | $0.00009 | $0.00145 |
Grade A, and why
spatial-patterns 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spatial Pattern Analysis
Overview
This skill answers: Which genes/features show significant spatial organization in this tissue?
Two complementary analyses:
- Spatially Variable Genes (SVG): Find genes with non-random spatial expression
- Spatial Statistics: Quantify and test spatial patterns
Decision Tree: Which Analysis?
Q: What do you want to know?
│
├─ Which genes have spatial patterns?
│ └─ SVG Detection
│ ├─ SpatialDE - Gaussian Process, handles noise well
│ ├─ SPARK-X - Fast, scalable to large datasets
│ └─ Moran's I per gene - Classic, interpretable
│
├─ Are spatial patterns statistically significant?
│ └─ Spatial Statistics
│ ├─ Global Moran's I - Overall spatial autocorrelation
│ ├─ Getis-Ord Gi* - Local hot/cold spot detection
│ └─ Ripley's K/L - Point pattern analysis
│
└─ Where are the spatial hotspots?
└─ Local Spatial Statistics
├─ LISA - Local Moran's I
└─ Getis-Ord Gi* - Hot spot analysis
Spatially Variable Gene Detection
Method Selection
| Method | Speed | Best For | Output |
|---|---|---|---|
| SpatialDE | Moderate | Noise robustness | p-values, effect sizes |
| SPARK-X | Fast | Large datasets (>50k spots) | p-values, adjusted |
| Moran's I | Fast | Simple interpretation | I statistic, p-value |
| Sepal | Moderate | Multi-scale patterns | Scale-specific genes |
Workflow
Step 1: Run SVG Detection
Use find_spatial_genes tool with:
method: "spatialDE", "sparkx", or "moran"n_top_genes: Number of top genes to return (default 100)
Step 2: Interpret Results
Key output columns:
pval/padj: Statistical significancemoranI/effect_size: Strength of spatial patterngene: Gene identifier
Filtering criteria:
Recommended thresholds:
- Adjusted p-value < 0.05 (stringent: < 0.01)
- Effect size > 0.1 (moderate spatial pattern)
- Expression level: Filter very low-expressed genes
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 · 191 lines · 90 tokens per session scan A f626ac332617
spatial-patterns is a skill published in the GitHub repository cafferychen777/ChatSpatial (45 stars, last pushed 2d ago), licensed MIT. It adds 90 tokens to every session and 1,450 once invoked, about $0.0004 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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