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Agent skill

Spatial Microenvironment Subset

by TianGzlab in TianGzlab/OmicsClaw

Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius…

Apache-2.0Auto-check passedResearch & Science

Install Spatial Microenvironment Subset

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill spatial-microenvironment-subset -a claude-code

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

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw spatial-microenvironment-subset --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/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/spatial/spatial-microenvironment-subset .claude/skills/spatial-microenvironment-subset && 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-microenvironment-subset
GitHub stars
161
Token cost
~1.2k tokens
SKILL.md length
396 words
Files
9 (incl. references)
Skills in repo
88
Repo updated
First seen
Licence
Apache-2.0

At a glance

Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius…

  • Research & Science work in your project
  • SKILL.md covers When to use, Use from a step, API and Methods and parameters, plus 5 more sections
  • Runs Python scripts from its folder; calls python

What it does

Spatial Microenvironment Subset is an agent skill from TianGzlab/OmicsClaw. Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius neighbours. Skip when running global tissue-domain detection (use spatial-domains); cross-condition comparison (use spatial-condition).

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `references/methodology.md`).

It sits in Research & Science. It works with AnnData. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

  • Research & Science work in your project

Example prompts

  • “/spatial-microenvironment-subset”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 90a3bec. 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

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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 Microenvironment Subset loads about 1.2k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 396 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

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 TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 396 words, ~1,202 tokens.

Download SKILL.mdSave it as .claude/skills/spatial-microenvironment-subset/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
spatial-microenvironment-subset
description
Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius neighbours. Skip when running global tissue-domain detection (use spatial-domains); cross-condition comparison (use spatial-condition).
trigger
microenvironment, neighborhood subset, spatial radius, neighboring cells, nearby cells, tumor microenvironment, extract cells within 50 microns
tags
spatial, microenvironment, niche, subsetting, neighbourhood, visium, xenium

spatial-microenvironment-subset

When to use

Extract centers and nearby observations. Use spatial-domains for global regions and spatial-condition for condition comparisons.

Use from a step

python
from skills._sdk.notebook import load_skill, read_input, write_output
library = load_skill("spatial-microenvironment-subset")
data = read_input("input.h5ad")
data = library.subset(data, center_key="cell_type", center_values=["Tumor"], radius_native=50)
write_output(library.selection_table(data), "tables/results.csv")

Run examples/example_step.py through the step runner.

API

<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->
subset(adata, *, center_values: list[str], center_key: str | None=None, radius_native: float | None=None, radius_microns: float | None=None, microns_per_coordinate_unit: float | None=None, data_type: str | None=None, include_centers: bool=True, target_key: str | None=None, target_values: list[str] | None=None)

Return a new neighborhood AnnData; expression matrices remain unchanged.

:param adata: Labelled AnnData with spatial coordinates; X, layers and raw are sliced. :param center_values: Labels defining centers, required as in the CLI. :param center_key: Label column; None selects the first recognized label column. :param radius_native: Positive coordinate-unit radius; default None requires radius_microns. :param radius_microns: Positive micron radius, exclusive with radius_native. :param microns_per_coordinate_unit: Explicit positive scale; None uses platform metadata. :param data_type: Optional platform hint used to resolve units, as in the CLI. :param include_centers: True retains centers regardless of the target-label filter. :param target_key: Optional neighbor label column; None uses the center column. :param target_values: Optional allowed neighbor labels; None admits all labels. :returns: A new AnnData with role, distance and JSON diagnostics. :raises ValueError: Invalid radius, labels, units, coordinates or an empty selection.

run_info(adata, *, keep: bool=True) -> dict

Read selection counts and resolved coordinate units.

:param adata: AnnData returned by subset. :param keep: True retains diagnostics; False removes them for CLI serialization. :returns: Selection diagnostics, or an empty dict before analysis.

Show full SKILL.md (170 more words)Show less
selection_table(adata)

Return coordinates, center identities and nearest-center distances.

:param adata: AnnData returned by subset; expression values are not read. :returns: One DataFrame row per selected observation. :raises KeyError: Selection columns are absent.

selection_figure(adata)

Plot selected centers and neighbors in coordinate units.

:param adata: AnnData returned by subset; reads coordinates and microenv_role. :returns: A matplotlib Figure without saving it. :raises KeyError: Selection roles are absent.

<!-- api:end -->

Methods and parameters

KD-tree distances select observations near a center. Exactly one native or micron radius is required; micron distances require known coordinate units. See parameters and methodology.

Gotchas

  • subset returns a copy and raises ValueError for missing centers or empty selections. selection_table adds micron distances only when a scale is known.
  • run_info(keep=False) removes library diagnostics before CLI serialization.

Inputs and outputs

The library returns AnnData, DataFrames or Figures without file writes. The CLI keeps reports, result.json, tables and conditional gallery outputs. See the complete output contract for filenames and conditions.

CLI

bash
python skills/spatial/spatial-microenvironment-subset/spatial_microenvironment_subset.py --input data.h5ad --output results/spatial-microenvironment-subset --center-values Tumor --radius-native 50

See also

Dependencies

anndata, matplotlib, numpy, pandas, scanpy, scipy

© TianGzlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (references) in skills/spatial/spatial-microenvironment-subset of TianGzlab/OmicsClaw.

  • SKILL.md
  • _api.py
  • examples/example_step.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • spatial_microenvironment_subset.py
  • tests/test_api.py
  • tests/test_spatial_microenvironment_subset.py

Open the folder on GitHubat commit 90a3bec

Compare with similar skills

Spatial Microenvironment Subset 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 Microenvironment Subset compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Spatial Microenvironment Subset this skillTianGzlab/OmicsClaw161—~1.2kAutomated safety check: PassApache-2.0
Scanpy Single-Cell Analysisdavila7/claude-code-templates32k16 repos~2.8kAutomated safety check: PassMIT
ScgptJimLiu/science-skills2274 repos~1.3kAutomated safety check: PassApache-2.0
PyDESeq2 Differential Expressiondavila7/claude-code-templates32k12 repos~4kAutomated safety check: PassMIT
Anndatadavila7/claude-code-templates32k12 repos~2.5kAutomated safety check: PassMIT
Single-Cell Initial AnalysisLigphiDonk/Oh-my--paper7381 repos~1.4kAutomated safety check: PassMIT

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Works with

Categories

Questions about Spatial Microenvironment Subset

What does Spatial Microenvironment Subset do?

Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius…. Spatial Microenvironment Subset is an agent skill from TianGzlab/OmicsClaw. Load when extracting a niche / microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius neighbours.

When should I use Spatial Microenvironment Subset?

Spatial Microenvironment Subset fits situations like: research & Science work in your project.

How do I install Spatial Microenvironment Subset in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill spatial-microenvironment-subset -a claude-code`. Or copy the skill folder (skills/spatial/spatial-microenvironment-subset in TianGzlab/OmicsClaw) into .claude/skills/spatial-microenvironment-subset in your project. Claude Code loads it when a task matches its description.

How do I install Spatial Microenvironment Subset in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill spatial-microenvironment-subset -a codex`. Or copy the skill folder (skills/spatial/spatial-microenvironment-subset in TianGzlab/OmicsClaw) into .agents/skills/spatial-microenvironment-subset in your project. Codex loads it when a task matches its description.

Can I use Spatial Microenvironment Subset 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 TianGzlab/OmicsClaw --skill spatial-microenvironment-subset -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-microenvironment-subset, .gemini/skills/spatial-microenvironment-subset, .github/skills/spatial-microenvironment-subset and .opencode/skills/spatial-microenvironment-subset in your project.

What does Spatial Microenvironment Subset need to run?

Going by SKILL.md and its folder, Spatial Microenvironment Subset needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Spatial Microenvironment Subset 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 Microenvironment Subset 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 Microenvironment Subset use?

Spatial Microenvironment Subset is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Spatial Microenvironment Subset use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 891 tokens, read only when the agent opens those files.

What are the alternatives to Spatial Microenvironment Subset?

Skills that share tags, products or a category with Spatial Microenvironment Subset: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 32k stars), Scgpt (JimLiu/science-skills, 227 stars), PyDESeq2 Differential Expression (davila7/claude-code-templates, 32k stars) and Anndata (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spatial Microenvironment Subset?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.

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