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Agent skill

Spatial S3 Domains SVG

by QING1105 in QING1105/ezST

Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes.

MITAuto-check passedBackend & APIs

Install Spatial S3 Domains SVG

skills CLI
$ npx skills add QING1105/ezST --skill spatial-s3-domains-svg -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install QING1105/ezST spatial-s3-domains-svg --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/QING1105/ezST.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/spatial-transcriptomics/skills/s3-domains-svg .claude/skills/spatial-s3-domains-svg && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
spatial-s3-domains-svg
GitHub stars
101
Token cost
~476 tokens
SKILL.md length
156 words
Files
1
Skills in repo
11
Repo updated
First seen
Licence
MIT

At a glance

Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes.

  • Works in 2 steps: Spatial domains:… → SVG detection:…
  • The user asks to find spatial domains/niches
  • SKILL.md covers Goal, Steps, Outputs and Biological Interpretation, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Spatial S3 Domains SVG is an agent skill from QING1105/ezST. Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes. Use when the user asks to find spatial domains/niches, run Moran's I, or detect spatially variable genes (SVGs) in Visium data. Produces spatial domain maps and SVG rankings, then stops for review.

Its SKILL.md is about 480 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Backend & APIs, covering File uploads and storage and Bioinformatics. The repository describes itself as: 10x Visium spatial transcriptomics analysis skills for Codex — staged workflow with human review gates and LLM biological interpretation. The licence is MIT.

When your agent uses it

  • The user asks to find spatial domains/niches
  • Detect spatially variable genes (SVGs) in Visium data

Example prompts

  • “/spatial-s3-domains-svg”

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. Spatial domains: identify_spatial_domains(adata_path=..., output_path=..., plot_path=..., resolution=..., n_neighs=...)
  2. SVG detection: find_spatially_variable_genes(adata_path=..., output_path=..., plot_path=..., n_top_genes=..., n_jobs=..., genes_to_plot=...)

What it can do on your machine

Read from SKILL.md and the folder at commit 429f9fc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Spatial S3 Domains SVG loads about 476 tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 156 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~476

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from QING1105/ezST at commit 429f9fc, republished under its MIT licence (© QING1105). 156 words, ~476 tokens.

Download SKILL.mdSave it as .claude/skills/spatial-s3-domains-svg/SKILL.md (or your agent's skills folder).
name
spatial-s3-domains-svg
description
Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes. Use when the user asks to find spatial domains/niches, run Moran's I, or detect spatially variable genes (SVGs) in Visium data. Produces spatial domain maps and SVG rankings, then stops for review.
license
MIT

S3 — Spatial Domains + SVG

Goal

Identify spatial domains (tissue architecture regions) using a spatial neighborhood graph, and detect spatially variable genes with Moran's I.

Steps

  1. Spatial domains: identify_spatial_domains(adata_path=..., output_path=..., plot_path=..., resolution=..., n_neighs=...)
    • Defaults: resolution=1.0, n_neighs=6 (spatial neighbor count).
    • Output: domain assignments + spatial domain map.
  2. SVG detection: find_spatially_variable_genes(adata_path=..., output_path=..., plot_path=..., n_top_genes=..., n_jobs=..., genes_to_plot=...)
    • Defaults: n_top_genes=100, n_jobs=1.
    • genes_to_plot: optional list of specific genes to visualize on spatial coordinates (useful for marker validation, e.g., EPCAM, CD3D, VIM).
    • Output: SVG ranked CSV + spatial plots of top genes.

Outputs

  • results/05_domains/<sample>_domains.h5ad
  • results/05_domains/<sample>_domains.png
  • results/06_svg/<sample>_svg_results.csv
  • results/06_svg/<sample>_svg_*.png

Biological Interpretation

  • Report the number of spatial domains and their spatial layout.
  • Interpret domains against expected tissue architecture (e.g., tumor core, stroma, immune infiltrate, normal epithelium).
  • Check top SVGs: are they known markers for the tissue type? Do their spatial patterns align with domains?

Stop for Review

Present interpretation using the template from the parent spatial-transcriptomics skill. Wait for 通过 / 调整 / 跳过 before proceeding to S4.

© QING1105, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/spatial-transcriptomics/skills/s3-domains-svg of QING1105/ezST.

Open the folder on GitHubat commit 429f9fc

Compare with similar skills

Spatial S3 Domains SVG next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Spatial S3 Domains SVG compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Spatial S3 Domains SVG this skillQING1105/ezST101—~476Automated safety check: PassMIT
Web Gallery Screenshot Maintenancesatoshikawato/gbdraw155—~6.2kAutomated safety check: PassMIT
Ena Databaseaipoch/medical-research-skills1.9k—~1.9kAutomated safety check: PassMIT
Snpeff Variant Annotationjaechang-hits/SciAgent-Skills3741 repos~5.4kAutomated safety check: PassMIT
Stripe Projectsfossasia/eventyay1.7k5 repos~2kAutomated safety check: NotesApache-2.0
FoundatioFoundatioFx/Foundatio2.1k—~3.9kAutomated safety check: PassApache-2.0

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More from QING1105/ezST

All 11 skills in this repo

  • Spatial Transcriptomics

    QING1105/ezST

    End-to-end 10x Visium spatial transcriptomics analysis workflow with staged execution and human review gates.

    101 GitHub stars~1.4k tokensUpdated 1 mo ago
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  • Spatial Visium Hd

    QING1105/ezST

    Visium HD platform branch of the spatial transcriptomics workflow — reconstruct single cells from 2 μm bins via morphological segmentation and bin-to-cell aggregation.

    101 GitHub stars~2.6k tokensUpdated 1 mo ago
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  • Spatial Atera

    QING1105/ezST

    Atera platform branch of the spatial transcriptomics workflow — load and validate Atera cell-level output (AnnData + Zarr segmentation) for downstream analysis.

    101 GitHub stars~576 tokensUpdated 1 mo ago
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  • Spatial S4 Deconvolve

    QING1105/ezST

    Stage 4 of the spatial transcriptomics workflow — deconvolve Visium spots into cell-type proportions.

    101 GitHub stars~480 tokensUpdated 1 mo ago
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  • Spatial S5 Downstream

    QING1105/ezST

    Stage 5 of the spatial transcriptomics workflow — neighborhood enrichment and cell-cell communication analysis.

    101 GitHub stars~513 tokensUpdated 1 mo ago
    Auto-check passed

  • Spatial Visium

    QING1105/ezST

    Classic Visium platform branch of the spatial transcriptomics workflow — spot-level 5-stage pipeline (load+QC, normalize+cluster, domains+SVG, deconvolution, downstream prep).

    101 GitHub stars~750 tokensUpdated 1 mo ago
    Auto-check passed

Categories

Questions about Spatial S3 Domains SVG

What does Spatial S3 Domains SVG do?

Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes. Spatial S3 Domains SVG is an agent skill from QING1105/ezST. Stage 3 of the spatial transcriptomics workflow — identify spatial domains and detect spatially variable genes.

When should I use Spatial S3 Domains SVG?

Spatial S3 Domains SVG fits situations like: the user asks to find spatial domains/niches; detect spatially variable genes (SVGs) in Visium data.

How do I install Spatial S3 Domains SVG in Claude Code?

Run `npx skills add QING1105/ezST --skill spatial-s3-domains-svg -a claude-code`. Or copy the skill folder (plugins/spatial-transcriptomics/skills/s3-domains-svg in QING1105/ezST) into .claude/skills/spatial-s3-domains-svg in your project. Claude Code loads it when a task matches its description.

How do I install Spatial S3 Domains SVG in Codex?

Run `npx skills add QING1105/ezST --skill spatial-s3-domains-svg -a codex`. Or copy the skill folder (plugins/spatial-transcriptomics/skills/s3-domains-svg in QING1105/ezST) into .agents/skills/spatial-s3-domains-svg in your project. Codex loads it when a task matches its description.

Can I use Spatial S3 Domains SVG in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add QING1105/ezST --skill spatial-s3-domains-svg -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spatial-s3-domains-svg, .gemini/skills/spatial-s3-domains-svg, .github/skills/spatial-s3-domains-svg and .opencode/skills/spatial-s3-domains-svg in your project.

What does Spatial S3 Domains SVG need to run?

SKILL.md names no scripts, command-line tools or credentials: Spatial S3 Domains SVG is instructions for the agent only.

Does Spatial S3 Domains SVG access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Spatial S3 Domains SVG safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Spatial S3 Domains SVG use?

Spatial S3 Domains SVG is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Spatial S3 Domains SVG use?

About 476 tokens (SKILL.md is roughly 1.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Spatial S3 Domains SVG?

Skills that share tags, products or a category with Spatial S3 Domains SVG: Web Gallery Screenshot Maintenance (satoshikawato/gbdraw, 155 stars), Ena Database (aipoch/medical-research-skills, 1.9k stars), Snpeff Variant Annotation (jaechang-hits/SciAgent-Skills, 374 stars) and Stripe Projects (fossasia/eventyay, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spatial S3 Domains SVG?

QING1105 (a GitHub user) maintains it in QING1105/ezST, which has 101 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on August 26, 2026.

Source: QING1105/ezST on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.