Agent skill

Spatial Deconv

Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others).

MITAuto-check passedResearch & Science

Install Spatial Deconv

skills CLI

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

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

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-deconv --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-deconv .claude/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .claude/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv

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-deconv -a codex

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

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-deconv --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-deconv .agents/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .agents/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv -a cursor

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

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-deconv --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-deconv .cursor/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .cursor/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv

--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-deconv -a gemini-cli

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

GitHub CLI

$ gh skill install TianGzlab/OmicsClaw spatial-deconv --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-deconv .gemini/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .gemini/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv

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-deconv -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-deconv .github/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .github/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv -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-deconv --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-deconv .opencode/skills/spatial-deconv && 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-deconv" agent skill from https://github.com/TianGzlab/OmicsClaw/tree/main/skills/spatial/spatial-deconv into .opencode/skills/spatial-deconv/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "spatial-deconv", 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-deconv
GitHub stars: 161
Token cost: ~1.9k tokens
SKILL.md length: 483 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 deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others).

Works in 5 steps: Load spatial AnnData + reference… → parser.error validates --input /… → Dispatch to method; method-specific… → …
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 Deconv is an agent skill from TianGzlab/OmicsClaw. Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others). Skip when each spot is a single cell already (Xenium / MERFISH) (use spatial-annotate); tissue-domain detection (use spatial-domains).

Its SKILL.md is about 1.9k 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 and scvi-tools. 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-deconv”

Requirements

Python 3

Workflow steps

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

Load spatial AnnData + reference (--reference .h5ad with cell-type labels). For flashdeconv reference is optional (uses internal heuristic).
parser.error validates --input / --reference / numeric flags (lines :300-350).
Dispatch to method; method-specific kwargs from METHOD_PARAM_DEFAULTS.
Build proportions matrix; compute per-spot dominant cell-type + Shannon diversity.
Save processed.h5ad (with obsm["proportions"]), tables, figures, report.md, result.json.

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 Deconv loads about 1.9k tokens when it runs, and up to ~6.7k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 483 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~85
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~6.7k

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). 483 words, ~1,874 tokens.

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

name: spatial-deconv
description: Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others). Skip when each spot is a single cell already (Xenium / MERFISH) (use spatial-annotate); tissue-domain detection (use spatial-domains).
version: 0.5.0
author: OmicsClaw
license: MIT
emoji: 🧩
tags: spatial, deconvolution, cell2location, rctd, destvi, stereoscope, tangram, spotlight, card, flashdeconv
requires: anndata, cell2location, flashdeconv, matplotlib, numpy, pandas, scanpy, scipy, scvi-tools, seaborn, tangram-sc, torch

spatial-deconv

When to use

The user has a Visium-style multi-cell-per-spot spatial AnnData PLUS a labelled scRNA reference AnnData and wants per-spot cell-type proportions. Eight backends:

flashdeconv (default) — ultra-fast O(N) CPU sketching. No GPU.
cell2location — Bayesian deep learning with spatial priors (--cell2location-n-epochs, --cell2location-detection-alpha, --cell2location-n-cells-per-spot). Requires scvi-tools + cell2location + torch.
rctd — Robust Cell Type Decomposition (R / spacexr).
destvi — multi-resolution VAE (--destvi-n-epochs, --destvi-n-hidden / --destvi-n-latent / --destvi-n-layers). Requires scvi-tools + torch.
stereoscope — two-stage probabilistic VAE (--stereoscope-learning-rate). Requires scvi-tools + torch.
tangram — gradient-based mapping (--tangram-n-epochs, --tangram-learning-rate). Requires tangram.
spotlight — NMF-based with marker-gene priors (--spotlight-n-top, --spotlight-min-prop, --spotlight-weight-id).
card — Conditional Autoregressive R-based deconvolution.

For single-cell-per-spot platforms (Xenium / MERFISH) use spatial-annotate. For tissue-region detection (no reference needed) use spatial-domains.

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/card_proportions.csv
tables/card_refined_proportions.csv
tables/celltype_diversity.csv
tables/deconv_run_summary.csv
tables/deconv_spatial_points.csv
tables/deconv_spot_metrics.csv
tables/deconv_umap_points.csv
tables/dominant_celltype.csv
tables/dominant_celltype_counts.csv
tables/mean_proportions.csv
tables/proportions.csv
tables/rctd_proportions.csv
tables/ref_celltypes.csv
tables/ref_counts.csv
tables/ref_meta.csv
tables/spatial_coords.csv
tables/spatial_counts.csv
tables/spotlight_proportions.csv
figures/assignment_margin_distribution.png
figures/assignment_margin_spatial.png
figures/celltype_diversity.png
figures/dominant_celltype.png
figures/dominant_celltype_distribution.png
figures/mean_proportions.png
figures/spatial_proportions.png
figures/umap_proportions.png
processed.h5ad
report.md
result.json
Processed AnnData (saves_h5ad) — adds obs: deconv_{method}_dominant_cell_type, deconv_{method}_dominant_proportion; obsm: deconvolution_{method}

Flow

Load spatial AnnData + reference (--reference .h5ad with cell-type labels). For flashdeconv reference is optional (uses internal heuristic).
parser.error validates --input / --reference / numeric flags (lines :300-350).
Dispatch to method; method-specific kwargs from METHOD_PARAM_DEFAULTS.
Build proportions matrix; compute per-spot dominant cell-type + Shannon diversity.
Save processed.h5ad (with obsm["proportions"]), tables, figures, report.md, result.json.

Show full SKILL.md (265 more words)Show less

Gotchas

All input + parameter validation goes through parser.error (exit code 2). spatial_deconv.py:300 for missing --input; :302 for missing input path; :306 for missing --reference on methods that need one; :308 for missing reference path; :335 and :338-350 for per-method numeric flag validation. Wrappers expecting ValueError need to catch exit-2.
--reference is required for almost every method (only flashdeconv can run without it). spatial_deconv.py:306 raises parser.error(f"--reference is required for method '{args.method}'") for the others. The reference must have cell-type labels in obs (key auto-resolved from common names).
Stored deconvolution-matrix lookup raises post-load. spatial_deconv.py:594 raises ValueError(f"Stored deconvolution matrix '<prop_key>' not found in adata.obsm") when re-rendering an already-deconvolved AnnData and the obsm key is missing. Used by the replot workflow.
obsm["spatial"] ↔ obsm["X_spatial"] sync at :534-536. Same dual-key pattern as spatial-domains — both keys exist after a run.
--cell2location-detection-alpha must be > 0. spatial_deconv.py:340 enforces. The cell2location default (typically 200) is a regularisation strength — lower values mean less spatial smoothing.
--destvi-dropout-rate is in [0, 1), not [0, 1]. spatial_deconv.py:342 enforces strict-less-than-1. dropout=1 would zero out everything.
R-backed methods (rctd, card) need a working R env. Both rely on R packages (spacexr for RCTD, CARD for CARD). Missing R deps surface as ImportError at runtime, not at preflight.

Key CLI

bash

# Demo (synthetic; flashdeconv default)
python omicsclaw.py run spatial-deconv --demo --output /tmp/spatial_deconv_demo

# FlashDeconv (CPU-only, fastest)
python omicsclaw.py run spatial-deconv \
  --input visium.h5ad --reference scrna_atlas.h5ad --output results/ \
  --method flashdeconv

# Cell2location (Bayesian, GPU)
python omicsclaw.py run spatial-deconv \
  --input visium.h5ad --reference scrna_atlas.h5ad --output results/ \
  --method cell2location --cell2location-n-epochs 30000 \
  --cell2location-n-cells-per-spot 8 --cell2location-detection-alpha 200

# RCTD (R-backed)
python omicsclaw.py run spatial-deconv \
  --input visium.h5ad --reference scrna_atlas.h5ad --output results/ \
  --method rctd --rctd-mode full

# Tangram (gradient mapping)
python omicsclaw.py run spatial-deconv \
  --input visium.h5ad --reference scrna_atlas.h5ad --output results/ \
  --method tangram --tangram-n-epochs 1000 --tangram-learning-rate 0.1

# CARD (Conditional Autoregressive R deconv)
python omicsclaw.py run spatial-deconv \
  --input visium.h5ad --reference scrna_atlas.h5ad --output results/ \
  --method card

Files

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

SKILL.md
r_visualization/README.md
r_visualization/deconv_publication_template.R
references/methodology.md
references/output_contract.md
references/parameters.md
skill.yaml
spatial_deconv.py
tests/test_spatial_deconv.py

Open the folder on GitHubat commit 6fbd79f

Compare with similar skills

Spatial Deconv 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 Deconv compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Spatial Deconv this skillTianGzlab/OmicsClaw	161	—	~1.9k	Automated safety check: Pass	MIT	2 mo ago
ScgptJimLiu/science-skills	227	4 repos	~1.3k	Automated safety check: Pass	Apache-2.0	3 mo ago
ScanpyK-Dense-AI/scientific-agent-skills	48k	1 repos	~5.1k	Automated safety check: Pass	BSD-3-Clause	2 days ago
Cellxgene CensusK-Dense-AI/scientific-agent-skills	48k	1 repos	~3.4k	Automated safety check: Notes	MIT	2 days ago
Anndata Data Structurejaechang-hits/SciAgent-Skills	370	2 repos	~5.8k	Automated safety check: Pass	BSD-3-Clause	9 days ago
AnndataK-Dense-AI/scientific-agent-skills	48k	1 repos	~3.9k	Automated safety check: Notes	BSD-3-Clause	2 days ago

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Questions about Spatial Deconv

What does Spatial Deconv do?

Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others). Spatial Deconv is an agent skill from TianGzlab/OmicsClaw. Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv / Cell2location / RCTD / DestVI / Tangram / others).

When should I use Spatial Deconv?

Spatial Deconv fits situations like: tasks that involve Bioinformatics.

How do I install Spatial Deconv in Claude Code?

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

How do I install Spatial Deconv in Codex?

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

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

What does Spatial Deconv need to run?

Going by SKILL.md and its folder, Spatial Deconv 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 Deconv 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 Deconv 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 Deconv use?

Spatial Deconv 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 Deconv use?

About 1.9k tokens (SKILL.md is roughly 7.5k 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 4.8k tokens, read only when the agent opens those files.

What are the alternatives to Spatial Deconv?

Skills that share tags, products or a category with Spatial Deconv: Scgpt (JimLiu/science-skills, 227 stars), Scanpy (K-Dense-AI/scientific-agent-skills, 48k stars), Cellxgene Census (K-Dense-AI/scientific-agent-skills, 48k stars) and Anndata Data Structure (jaechang-hits/SciAgent-Skills, 370 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spatial Deconv?

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 Deconv

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-deconv

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 Deconv