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Agent skill

Scrna Orchestrator

by FreedomIntelligence in FreedomIntelligence/OpenClaw-Medical-Skills

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

MITAuto-check passedResearch & Science

Install Scrna Orchestrator

skills CLI
$ npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scrna-orchestrator -a claude-code

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

GitHub CLI
$ gh skill install FreedomIntelligence/OpenClaw-Medical-Skills scrna-orchestrator --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/FreedomIntelligence/OpenClaw-Medical-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scrna-orchestrator .claude/skills/scrna-orchestrator && 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
scrna-orchestrator
GitHub stars
3.1k
Token cost
~1.7k tokens
SKILL.md length
511 words
Files
3
Skills in repo
279
Repo updated
First seen
Licence
MIT

At a glance

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

  • Works in 7 steps: QC and Filtering: Mitochondrial… → Preprocessing: Library-size… → Embedding and Clustering: PCA, neighbors… → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers Why This Exists, Core Capabilities, Input Formats and Workflow, plus 9 more sections
  • Runs Python scripts from its folder; calls python

What it does

Scrna Orchestrator is an agent skill from FreedomIntelligence/OpenClaw-Medical-Skills. Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `scrna_orchestrator.py` and `tests/test_scrna_orchestrator.py`).

It sits in Research & Science, covering Bioinformatics. It works with Scanpy. The repository describes itself as: The largest open-source medical AI skills library for OpenClaw🦞. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “/scrna-orchestrator”

Requirements

  • Python 3

Workflow steps

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

  1. QC and Filtering: Mitochondrial percentage filtering and min genes/cells thresholds.
  2. Preprocessing: Library-size normalization, log1p, and HVG selection.
  3. Embedding and Clustering: PCA, neighbors graph, UMAP, Leiden clustering.
  4. Cluster Markers: Wilcoxon cluster-vs-rest marker detection.
  5. Optional Group DE (v1): Two-group Wilcoxon DE on any obs column.
  6. Optional Volcano Plot: Generate DE volcano plot with --de-volcano.
  7. Reporting: Markdown report, CSV/TSV tables, PNG figures, reproducibility files.

What it can do on your machine

Read from SKILL.md and the folder at commit b1f9b6e. 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

    Links to these hosts (documentation or services it may open):

    • scanpy.readthedocs.io
    • anndata.readthedocs.io
    • nature.com

    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

Scrna Orchestrator loads about 1.7k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 511 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

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 FreedomIntelligence/OpenClaw-Medical-Skills at commit b1f9b6e, republished under its MIT licence (© FreedomIntelligence). 511 words, ~1,692 tokens.

Download SKILL.mdSave it as .claude/skills/scrna-orchestrator/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
scrna-orchestrator
description
Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad.
version
0.1.0
author
Yonghao Zhao
license
MIT
tags
scrna, single-cell, scanpy, clustering, differential-expression

🦖 scRNA Orchestrator

You are scRNA Orchestrator, a specialised ClawBio agent for local single-cell RNA-seq analysis with Scanpy.

Why This Exists

Single-cell workflows are easy to misconfigure and hard to reproduce when run ad hoc.

  • Without it: Users manually stitch QC, normalization, clustering, and marker/DE steps with inconsistent defaults.
  • With it: One command produces a consistent report.md, figures, tables, and reproducibility bundle.
  • Why ClawBio: The workflow is local-first, explicit about assumptions (raw counts), and ships machine-readable outputs.

Core Capabilities

  1. QC and Filtering: Mitochondrial percentage filtering and min genes/cells thresholds.
  2. Preprocessing: Library-size normalization, log1p, and HVG selection.
  3. Embedding and Clustering: PCA, neighbors graph, UMAP, Leiden clustering.
  4. Cluster Markers: Wilcoxon cluster-vs-rest marker detection.
  5. Optional Group DE (v1): Two-group Wilcoxon DE on any obs column.
  6. Optional Volcano Plot: Generate DE volcano plot with --de-volcano.
  7. Reporting: Markdown report, CSV/TSV tables, PNG figures, reproducibility files.

Input Formats

FormatExtensionRequired FieldsExample
AnnData raw counts.h5adRaw count matrix in X; cell metadata in obs; gene metadata in varpbmc_raw.h5ad
Demo moden/anonepython clawbio.py run scrna --demo

Notes:

  • Processed/normalized/scaled .h5ad inputs are rejected with an actionable error.
  • pbmc3k_processed-style inputs are out of scope for this skill.

Workflow

When the user asks for scRNA QC/clustering/markers/DE:

  1. Validate: Check .h5ad input (or --demo), and reject processed-like matrices.
  2. Process: Run QC filtering, normalization, HVG selection, PCA, neighbors, UMAP, and Leiden.
  3. Analyze:
  • Always run cluster marker analysis (leiden, Wilcoxon).
  • Optionally run DE if --de-groupby --de-group1 --de-group2 are all provided.
  1. Generate: Write report.md, result.json, tables, figures, and reproducibility bundle.

CLI Reference

bash
# Standard usage
python skills/scrna-orchestrator/scrna_orchestrator.py \
  --input <input.h5ad> --output <report_dir>

# Demo mode
python skills/scrna-orchestrator/scrna_orchestrator.py \
  --demo --output <report_dir>

# Optional two-group DE
python skills/scrna-orchestrator/scrna_orchestrator.py \
  --input <input.h5ad> --output <report_dir> \
  --de-groupby <obs_column> --de-group1 <group_a> --de-group2 <group_b>

# Optional DE volcano plot
python skills/scrna-orchestrator/scrna_orchestrator.py \
  --input <input.h5ad> --output <report_dir> \
  --de-groupby <obs_column> --de-group1 <group_a> --de-group2 <group_b> \
  --de-volcano

# Via ClawBio runner
python clawbio.py run scrna --input <input.h5ad> --output <report_dir>
python clawbio.py run scrna --demo

Demo

bash
python clawbio.py run scrna --demo

Expected output:

  • report.md with QC, clustering, and marker summaries
  • figure files (qc_violin.png, umap_leiden.png, marker_dotplot.png)
  • optional DE figure (de_volcano.png) when --de-volcano is set
  • marker tables and reproducibility bundle
Show full SKILL.md (221 more words)Show less

Algorithm / Methodology

  1. QC:
  • Compute QC metrics (n_genes_by_counts, total_counts, pct_counts_mt)
  • Filter by min_genes, min_cells, max_mt_pct
  1. Preprocess:
  • Normalize total counts to 1e4
  • Apply log1p
  • Select HVGs (flavor="seurat")
  1. Embed and cluster:
  • Scale (max_value=10)
  • PCA, neighbors graph, UMAP
  • Leiden clustering
  1. Markers:
  • scanpy.tl.rank_genes_groups(groupby="leiden", method="wilcoxon", pts=True)
  1. Optional DE v1:
  • scanpy.tl.rank_genes_groups(groupby=<de_groupby>, groups=[group1], reference=group2, method="wilcoxon", pts=True)
  • Export full statistics and top genes by score
  1. Optional volcano plot:
  • Plot logfoldchanges vs -log10(pvals_adj) (fallback to pvals if needed)
  • Highlight genes with p < 0.05 and |log2FC| >= 1

Example Queries

  • "Run standard QC and clustering on my h5ad file"
  • "Find marker genes for each cluster"
  • "Generate a UMAP coloured by cluster"
  • "Run differential expression for treated vs control"

Output Structure

text
output_directory/
├── report.md
├── result.json
├── figures/
│   ├── qc_violin.png
│   ├── umap_leiden.png
│   ├── marker_dotplot.png
│   └── de_volcano.png    # only when DE volcano is enabled
├── tables/
│   ├── cluster_summary.csv
│   ├── markers_top.csv
│   ├── markers_top.tsv
│   ├── de_full.csv      # only when DE is enabled
│   └── de_top.csv       # only when DE is enabled
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    └── checksums.sha256

Dependencies

Required:

  • scanpy >= 1.10
  • anndata >= 0.10
  • numpy, pandas, matplotlib, leidenalg, python-igraph

Optional (future):

  • celltypist (cell-type annotation)
  • scvi-tools (deep generative modeling)

Safety

  • Local-first: No patient data upload.
  • Disclaimer: Reports include the ClawBio medical disclaimer.
  • Input guardrails: Rejects processed-like matrices to reduce invalid biological inferences.
  • Reproducibility: Writes command/environment/checksum bundle.

Integration with Bio Orchestrator

Trigger conditions:

  • File extension .h5ad
  • User intent includes scRNA terms (single-cell, Scanpy, clustering, marker genes, DE)

Current limitations:

  • Raw-count .h5ad only
  • Seurat input/output is not implemented in Python path
  • Multi-group pairwise DE, within-cluster DE, and automated annotation are future work

Citations

© FreedomIntelligence, MIT. 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 2 other files in skills/scrna-orchestrator of FreedomIntelligence/OpenClaw-Medical-Skills.

  • SKILL.md
  • scrna_orchestrator.py
  • tests/test_scrna_orchestrator.py

Open the folder on GitHubat commit b1f9b6e

Compare with similar skills

Scrna Orchestrator 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.

Scrna Orchestrator compared with similar skills
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Single Cell Rna AnalysisPKU-YuanGroup/OpenAI4S620—~1.3kAutomated safety check: PassMIT
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Works with

Categories

Questions about Scrna Orchestrator

What does Scrna Orchestrator do?

Local Scanpy pipeline for single-cell RNA-seq QC, clustering, marker discovery, and optional two-group differential expression from raw-count .h5ad. Scrna Orchestrator is an agent skill from FreedomIntelligence/OpenClaw-Medical-Skills.h5ad.

When should I use Scrna Orchestrator?

Scrna Orchestrator fits situations like: tasks that involve Bioinformatics.

How do I install Scrna Orchestrator in Claude Code?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scrna-orchestrator -a claude-code`. Or copy the skill folder (skills/scrna-orchestrator in FreedomIntelligence/OpenClaw-Medical-Skills) into .claude/skills/scrna-orchestrator in your project. Claude Code loads it when a task matches its description.

How do I install Scrna Orchestrator in Codex?

Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill scrna-orchestrator -a codex`. Or copy the skill folder (skills/scrna-orchestrator in FreedomIntelligence/OpenClaw-Medical-Skills) into .agents/skills/scrna-orchestrator in your project. Codex loads it when a task matches its description.

Can I use Scrna Orchestrator 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 FreedomIntelligence/OpenClaw-Medical-Skills --skill scrna-orchestrator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scrna-orchestrator, .gemini/skills/scrna-orchestrator, .github/skills/scrna-orchestrator and .opencode/skills/scrna-orchestrator in your project.

What does Scrna Orchestrator need to run?

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

Does Scrna Orchestrator access the network?

SKILL.md names 3 domains. As links in the text: scanpy.readthedocs.io, anndata.readthedocs.io and nature.com. This is read from the text; nothing was executed.

Is Scrna Orchestrator 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 Scrna Orchestrator use?

Scrna Orchestrator 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 Scrna Orchestrator use?

About 1.7k tokens (SKILL.md is roughly 6.8k 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 Scrna Orchestrator?

Skills that share tags, products or a category with Scrna Orchestrator: Scanpy Single-Cell Analysis (davila7/claude-code-templates, 32k stars), Single Cell Rna Analysis (PKU-YuanGroup/OpenAI4S, 620 stars), Anndata (davila7/claude-code-templates, 32k stars) and Cellxgene Census (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 Scrna Orchestrator?

FreedomIntelligence (a GitHub organization) maintains it in FreedomIntelligence/OpenClaw-Medical-Skills, which has 3,052 GitHub stars. The repository holds 279 skills in this directory. The repository was last updated on July 21, 2026.

Source: FreedomIntelligence/OpenClaw-Medical-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.