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 CHENyiru3/AI-Skills-Collections --skill giottogit clone --depth 1 https://github.com/CHENyiru3/AI-Skills-CollectionsWrote 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/chenyiru3/ai-skills-collections/giotto)<a href="https://agentmods.dev/skills/chenyiru3/ai-skills-collections/giotto"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/giotto/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/chenyiru3/ai-skills-collections/giotto"><img src="https://agentmods.dev/badge/skills/chenyiru3/ai-skills-collections/giotto.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 | $0.00023 | $0.00724 |
| Opus 5.5 | $0.00009 | $0.00290 |
| Sonnet 5.5 | $0.00005 | $0.00145 |
| Haiku 4.5 | $0.00002 | $0.00072 |
Grade A, and why
giotto 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.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Giotto: Spatial Genomics Toolkit
Overview
Giotto is a comprehensive R toolkit for spatial genomics, supporting multiple platforms (Visium, Slide-seq, MERFISH, seqFISH, Xenium) with advanced analysis and visualization capabilities.
When to Use This Skill
This skill should be used when:
- Analyzing spatial transcriptomics data in R
- Working with multiple spatial platforms
- Performing advanced spatial statistics
- Creating publication-quality visualizations
- Integrating spatial and single-cell data
- Working with large-scale spatial datasets
Quick Start
Installation
# Install Giotto
install.packages("Giotto")
# Or from GitHub
devtools::install_github("rubd/GiottoSuite")
devtools::install_github("rubd/Giotto")
# Install spatial packages
install.packages("magick") # For image handling
Basic Setup
library(Giotto)
library(ggplot2)
library(data.table)
Creating Giotto Objects
From Visium
# Load Visium data
expr_path <- "raw_feature_bc_matrix/"
image_path <- "spatial/"
json_path <- "spatial/tissue_positions.json"
# Create Giotto object
visium.g <- createGiottoObject(
raw_expr = expr_path,
spatial_locs = NULL,
image = image_path
)
# Or from Seurat
# Convert Seurat to Giotto
library(Seurat)
seurat.obj <- Load10X_Spatial("visium_data/")
visium.g <- seuratToGiotto(seurat.obj)
From Custom Data
# From expression matrix
expr_mat <- read.csv("expression.csv", row.names = 1)
loc_df <- read.csv("coordinates.csv")
# Create Giotto object
gobject <- createGiottoObject(
raw_expr = expr_mat,
spatial_locs = loc_df
)
Spatial Analysis
Spatial Network
# Create spatial network
gobject <- createSpatialNetwork(
gobject,
method = "knn",
k = 6
)
# View network
showGiottoNetwork(gobject)
Spatial Statistics
# Various spatial statistics available
# See Giotto documentation for full list
Visualization
Spatial Plots
# Basic spatial plot
spatPlot(gobject, cell_color = "cell_type")
# With image background
spatPlot(
gobject,
cell_color = "cluster",
image = TRUE,
save_param = list(save_name = "spatial_plot")
)
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 · 147 lines · 23 tokens per session scan A 624aa0bf9463
giotto is a skill published in the GitHub repository CHENyiru3/AI-Skills-Collections (1 stars, last pushed 7d ago), licensed MIT. It adds 23 tokens to every session and 724 once invoked, about $0.0001 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 2026-10-02.
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