Agent skill

Spatial Communication

Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with obs[celltypekey] (default leiden) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R).

MITAuto-check passedResearch & Science

Install Spatial Communication

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a claude-code

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

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication --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-communication .claude/skills/spatial-communication && 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/

Paste into Claude Code

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .claude/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/spatial/spatial-communication .agents/skills/spatial-communication && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .agents/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/spatial/spatial-communication .cursor/skills/spatial-communication && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .cursor/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/TianGzlab/OmicsClaw.git --path skills/spatial/spatial-communication

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/spatial/spatial-communication .gemini/skills/spatial-communication && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .gemini/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/spatial/spatial-communication .github/skills/spatial-communication && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .github/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add TianGzlab/OmicsClaw --skill spatial-communication -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-communication --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/spatial/spatial-communication .opencode/skills/spatial-communication && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "spatial-communication" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-communication into .opencode/skills/spatial-communication/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-communication", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: spatial-communication
GitHub stars: 161
Token cost: ~1.6k tokens
SKILL.md length: 391 words
Files: 9 (incl. references)
Skills in repo: 95
Repo updated: Jul 28, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with obs[celltypekey] (default leiden) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R).

Works in 6 steps: Load AnnData, validate… → Sync obsm["spatial"] ↔ obsm["X_spatial"]… → Dispatch to chosen backend (LIANA /… → …
Tasks that involve Bioinformatics
SKILL.md covers When to use, Inputs & Outputs, Flow and Gotchas, plus 2 more sections
Runs Python and R scripts from its folder; calls python

What it does

Spatial Communication is an agent skill from TianGzlab/OmicsClaw. Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with obs[celltypekey] (default leiden) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R). Skip when running scRNA-only L-R inference (use sc-cell-communication); no cell-type labels exist (use spatial-annotate).

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `r_visualization/README.md`, `references/methodology.md` and `references/output_contract.md`).

It sits in Research & Science, covering Bioinformatics. 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 MIT.

When your agent uses it

Tasks that involve Bioinformatics

Example prompts

“/spatial-communication”

Requirements

Python 3

Workflow steps

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

Load AnnData, validate obs[cell_type_key] exists with ≥ 2 categories (_lib/communication.py:764-765).
Sync obsm["spatial"] ↔ obsm["X_spatial"] (spatial_communication.py:79-81); cast cell-type column to Categorical.
Dispatch to chosen backend (LIANA / CellPhoneDB / FastCCC / CellChat-R).
Write canonical L-R results to uns["ccc_results"] + per-method uns[METHOD_RESULT_KEYS[method]] (_lib/communication.py:735-739).
Compute pathway-level summary, signaling roles, source-target summary.
Save tables + processed.h5ad + report.

What it can do on your machine

Read from SKILL.md and the folder at commit 6fbd79f. 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 and R), 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 Communication loads about 1.6k tokens when it runs, and up to ~5.6k if it reads all its reference files. Until then it costs about 86 tokens; SKILL.md has 391 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~86
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~5.6k

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 6fbd79f, republished under its MIT licence (© TianGzlab). 391 words, ~1,641 tokens.

Download SKILL.mdSave it as .claude/skills/spatial-communication/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.

name: spatial-communication
description: Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with `obs[cell_type_key]` (default `leiden`) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R). Skip when running scRNA-only L-R inference (use sc-cell-communication); no cell-type labels exist (use spatial-annotate).
version: 0.5.0
author: OmicsClaw
license: MIT
emoji: 📡
tags: spatial, communication, ligand-receptor, liana, cellphonedb, cellchat, fastccc
requires: anndata, cellphonedb, fastccc, liana, matplotlib, numpy, pandas, scanpy, scipy, seaborn

spatial-communication

When to use

The user has a preprocessed spatial AnnData with cell-type labels (obs[cell_type_key], default leiden) and wants ligand-receptor cell-cell communication scored. Four backends:

liana (default) — LIANA consensus across multiple L-R methods. Tunables --liana-expr-prop, --liana-min-cells, --liana-n-perms.
cellphonedb — Permutation test with mean expression statistic. Tunables --cellphonedb-iterations, --cellphonedb-threshold.
fastccc — Fast permutation-free percentile-based score. Tunables --fastccc-min-percentile.
cellchat_r — CellChat (R) via rpy2 interop. Tunables --cellchat-min-cells, --cellchat-prob-type.

Species: --species human (default) or mouse. For non-spatial L-R use sc-cell-communication; for pathway scoring use spatial-enrichment.

Inputs & Outputs

<!-- AUTO-GENERATED from skill.yaml (interface) — do not edit by hand. Regenerate: python scripts/generate_skill_md.py <skill_dir> -->

Inputs

File types: .h5ad
Requires a preprocessed AnnData (X normalised, PCA/neighbours present)
Expects obsm: spatial

Outputs

tables/cellchat_centrality.csv
tables/cellchat_count_matrix.csv
tables/cellchat_pathways.csv
tables/cellchat_results.csv
tables/cellchat_weight_matrix.csv
tables/communication_run_summary.csv
tables/communication_spatial_points.csv
tables/communication_summary.csv
tables/communication_umap_points.csv
tables/complex_composition_table.csv
tables/complex_table.csv
tables/gene_table.csv
tables/interaction_table.csv
tables/lr_interactions.csv
tables/meta.tsv
tables/protein_table.csv
tables/signaling_roles.csv
tables/source_target_summary.csv
tables/top_interactions.csv
figures/communication_pvalue_distribution.png
figures/communication_roles_spatial.png
figures/communication_score_vs_significance.png
figures/lr_dotplot.png
figures/lr_heatmap.png
figures/lr_spatial.png
figures/signaling_roles.png
figures/source_target_summary.png
fastccc_input.h5ad
input.h5ad
processed.h5ad
report.md
result.json
Processed AnnData (saves_h5ad) — adds uns: ccc_results, liana_results, cellphonedb_results, fastccc_results, cellchat_results, communication_summary, communication_signaling_roles, spatial_communication

Flow

Load AnnData, validate obs[cell_type_key] exists with ≥ 2 categories (_lib/communication.py:764-765).
Sync obsm["spatial"] ↔ obsm["X_spatial"] (spatial_communication.py:79-81); cast cell-type column to Categorical.
Dispatch to chosen backend (LIANA / CellPhoneDB / FastCCC / CellChat-R).
Write canonical L-R results to uns["ccc_results"] + per-method uns[METHOD_RESULT_KEYS[method]] (_lib/communication.py:735-739).
Compute pathway-level summary, signaling roles, source-target summary.
Save tables + processed.h5ad + report.

Show full SKILL.md (196 more words)Show less

Gotchas

obs[cell_type_key] is REQUIRED — no auto-fallback. _lib/communication.py:764-765 raises ValueError when the column is missing. Run spatial-annotate or spatial-domains first.
Default cell-type column is leiden, not cell_type. spatial_communication.py:1065 defaults --cell-type-key to "leiden". If your AnnData uses cell_type, pass --cell-type-key cell_type explicitly.
CellChat backend needs an R install with CellChat. --method cellchat_r invokes R via rpy2. Install CellChat in your R environment first; missing R / rpy2 / CellChat surfaces as a runtime error inside the dispatch step (not at parser.error), so the failure happens after argument parsing succeeds.
FastCCC --fastccc-min-percentile must be in [0, 1]. spatial_communication.py:985 rejects values outside that range with parser.error.
Output uns keys are unconditionally written, even with 0 interactions. _lib/communication.py:735-739 writes empty uns["ccc_results"] / uns["communication_summary"] if no L-R pairs pass thresholds — distinguish "no signal" from "method failed" by inspecting tables/communication_run_summary.csv.
Per-method copy uses METHOD_RESULT_KEYS mapping. _lib/communication.py:68-73 maps liana → uns["liana_results"], cellphonedb → uns["cellphonedb_results"], fastccc → uns["fastccc_results"], cellchat_r → uns["cellchat_results"]. Downstream readers should prefer uns["ccc_results"] for portability.

Key CLI

bash

# Demo
python omicsclaw.py run spatial-communication --demo --output /tmp/comm_demo

# LIANA consensus (default)
python omicsclaw.py run spatial-communication \
  --input preprocessed.h5ad --output results/ \
  --method liana --species human --cell-type-key cell_type \
  --liana-expr-prop 0.1 --liana-min-cells 5 --liana-n-perms 1000

# CellPhoneDB permutation test
python omicsclaw.py run spatial-communication \
  --input preprocessed.h5ad --output results/ \
  --method cellphonedb --cellphonedb-iterations 1000 --cellphonedb-threshold 0.1

# CellChat (R via rpy2)
python omicsclaw.py run spatial-communication \
  --input preprocessed.h5ad --output results/ \
  --method cellchat_r --species mouse \
  --cellchat-min-cells 10 --cellchat-prob-type triMean

Files

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

SKILL.md
r_visualization/README.md
r_visualization/communication_publication_template.R
references/methodology.md
references/output_contract.md
references/parameters.md
skill.yaml
spatial_communication.py
tests/test_spatial_communication.py

Open the folder on GitHubat commit 6fbd79f

Compare with similar skills

Spatial Communication 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 Communication compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Spatial Communication this skillTianGzlab/OmicsClaw	161	—	~1.6k	Automated safety check: Pass	MIT	2 mo ago
Scanpy Single-Cell Analysisdavila7/claude-code-templates	32k	16 repos	~2.8k	Automated safety check: Pass	MIT	today
ScgptJimLiu/science-skills	227	4 repos	~1.3k	Automated safety check: Pass	Apache-2.0	3 mo ago
PyDESeq2 Differential Expressiondavila7/claude-code-templates	32k	12 repos	~4k	Automated safety check: Pass	MIT	today
Anndatadavila7/claude-code-templates	32k	12 repos	~2.5k	Automated safety check: Pass	MIT	today
Single-Cell Initial AnalysisLigphiDonk/Oh-my--paper	738	1 repos	~1.4k	Automated safety check: Pass	MIT	5 mo ago

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Questions about Spatial Communication

What does Spatial Communication do?

Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with obs[celltypekey] (default leiden) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R). Spatial Communication is an agent skill from TianGzlab/OmicsClaw. Load when computing ligand-receptor cell-cell communication on a preprocessed spatial AnnData with obs[celltypekey] (default leiden) via LIANA (default), CellPhoneDB, FastCCC, or CellChat (R).

When should I use Spatial Communication?

Spatial Communication fits situations like: tasks that involve Bioinformatics.

How do I install Spatial Communication in Claude Code?

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

How do I install Spatial Communication in Codex?

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

Can I use Spatial Communication 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-communication -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-communication, .gemini/skills/spatial-communication, .github/skills/spatial-communication and .opencode/skills/spatial-communication in your project.

What does Spatial Communication need to run?

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

Does Spatial Communication 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 Communication 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 Communication use?

Spatial Communication 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 Communication use?

About 1.6k tokens (SKILL.md is roughly 6.6k 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 4k tokens, read only when the agent opens those files.

What are the alternatives to Spatial Communication?

Skills that share tags, products or a category with Spatial Communication: 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 Communication?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 95 skills in this directory. The repository was last updated on July 28, 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.

Install Spatial Communication

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

spatial-communication

When to use

Inputs & Outputs

Flow

Gotchas

Key CLI

See also

Files

Compare with similar skills

Similar skills

More from TianGzlab/OmicsClaw

Related

Questions about Spatial Communication