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Agent skill

Sc Multi Count

by TianGzlab in TianGzlab/OmicsClaw

Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels.

MITAuto-check passedResearch & Science

Install Sc Multi Count

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill sc-multi-count -a claude-code

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

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw sc-multi-count --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/singlecell/scrna/sc-multi-count .claude/skills/sc-multi-count && 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
sc-multi-count
GitHub stars
161
Token cost
~1.2k tokens
SKILL.md length
366 words
Files
8 (incl. references)
Skills in repo
95
Repo updated
First seen
Licence
MIT

At a glance

Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels.

  • Works in 6 steps: Collect per-sample AnnData paths from… → Load each, normalise the single-cell… → Stack with explicit sample-label per cell. → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers When to use, Inputs & Outputs, Flow and Gotchas, plus 2 more sections
  • Runs Python scripts from its folder; calls python

What it does

Sc Multi Count is an agent skill from TianGzlab/OmicsClaw. Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels. Skip when input is one already-merged AnnData (use sc-standardize-input); FASTQ→counts on each sample (use sc-count).

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/methodology.md`, `references/output_contract.md` and `references/parameters.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

  • “/sc-multi-count”

Requirements

  • Python 3

Workflow steps

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

  1. Collect per-sample AnnData paths from each --input flag (action="append"); paired --sample-id flags assign sample labels.
  2. Load each, normalise the single-cell contract (layers["counts"], adata.raw, gene name harmonisation).
  3. Stack with explicit sample-label per cell.
  4. Write merged AnnData; emit per-sample / per-barcode summary tables.
  5. Render barcode-rank + composition figures.
  6. Emit 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), 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

Sc Multi Count loads about 1.2k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 72 tokens; SKILL.md has 366 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
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
~3k

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). 366 words, ~1,186 tokens.

Download SKILL.mdSave it as .claude/skills/sc-multi-count/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
sc-multi-count
description
Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels. Skip when input is one already-merged AnnData (use sc-standardize-input); FASTQ→counts on each sample (use sc-count).
version
0.3.0
author
OmicsClaw
license
MIT
emoji
🧬
tags
singlecell, scrna, multi-sample, merge, aggregation
requires
anndata, matplotlib, numpy, pandas, scanpy, scipy, seaborn

sc-multi-count

When to use

The user has run sc-count (or another counting backend) on multiple samples separately and now needs them merged into one AnnData with a canonical sample-label column for downstream batch-aware analysis. Replaces cellranger aggr for the OmicsClaw pipeline — preserves the canonical AnnData contract instead of re-counting.

Inputs & Outputs

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

Inputs

  • Modalities: scrna

Outputs

  • tables/Summary.csv
  • tables/barcode_metrics.csv
  • tables/barcodes.tsv
  • tables/cell_metadata.csv
  • tables/features.tsv
  • tables/genes.tsv
  • tables/metrics_summary.csv
  • tables/per_sample_summary.csv
  • figures/barcode_rank.png
  • figures/count_complexity_scatter.png
  • figures/count_distributions.png
  • figures/sample_composition.png
  • 3M-february-2018.txt
  • 737K-august-2016.txt
  • Aligned.sortedByCoord.out.bam
  • analysis_summary.txt
  • multiqc_report.html
  • possorted_genome_bam.bam
  • processed.h5ad
  • standardized_input.h5ad
  • web_summary.html
  • report.md
  • result.json
  • Processed AnnData (saves_h5ad) — adds obs: sample_id

Flow

  1. Collect per-sample AnnData paths from each --input <path> flag (action="append"); paired --sample-id <id> flags assign sample labels.
  2. Load each, normalise the single-cell contract (layers["counts"], adata.raw, gene name harmonisation).
  3. Stack with explicit sample-label per cell.
  4. Write merged AnnData; emit per-sample / per-barcode summary tables.
  5. Render barcode-rank + composition figures.
  6. Emit report.md + result.json.

Gotchas

  • --input is action="append" — repeat the flag, do not comma-split. sc_multi_count.py:315 declares --input with action="append". Pass --input s1.h5ad --input s2.h5ad --input s3.h5ad; a single comma-separated value (--input s1.h5ad,s2.h5ad) is treated as one literal path that does not exist and triggers FileNotFoundError. No directory expansion.
  • At least two --input paths are required. sc_multi_count.py:335 calls parser.error("At least two --input paths required when not using --demo.") if you pass zero or one. For a single-sample run you don't need this skill — just use the upstream sc-count output directly.
  • Missing input file → hard fail. sc_multi_count.py:346 raises FileNotFoundError when any individual --input path does not resolve. In batch pipelines, a single mistyped sample name aborts the whole merge — pre-flight your file list.
  • --r-enhanced is accepted but produces no R plots. This skill emits Python figures only; the flag exists for CLI consistency.
  • No within-sample re-counting. This is a stitching skill — it stacks already-canonical AnnData objects. If a per-sample input has a non-canonical matrix layout, run sc-standardize-input on each before this; otherwise the merged contract may surface incoherent per-cell metrics downstream.
Show full SKILL.md (51 more words)Show less

Key CLI

bash
# Demo (built-in two synthetic samples)
python omicsclaw.py run sc-multi-count --demo --output /tmp/sc_multi_demo

# Three samples — repeat --input per file
python omicsclaw.py run sc-multi-count \
  --input s1.h5ad --input s2.h5ad --input s3.h5ad \
  --output results/

# With explicit per-sample labels (paired with --input order)
python omicsclaw.py run sc-multi-count \
  --input s1.h5ad --sample-id ctrl_a \
  --input s2.h5ad --sample-id ctrl_b \
  --input s3.h5ad --sample-id treat_a \
  --output results/

See also

  • references/parameters.md — every CLI flag and tuning hint
  • references/methodology.md — sample-label derivation, contract harmonisation rules
  • references/output_contract.md — merged obs schema, table layout
  • Adjacent skills: sc-count (upstream — produces single-sample AnnData inputs), sc-standardize-input (per-sample contract canonicaliser, run before this when inputs are external), sc-batch-integration (downstream — corrects batch effects in the merged AnnData)

© TianGzlab, 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 7 other files (references) in skills/singlecell/scrna/sc-multi-count of TianGzlab/OmicsClaw.

  • SKILL.md
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • references/r_visualization.md
  • sc_multi_count.py
  • skill.yaml
  • tests/test_sc_multi_count.py

Open the folder on GitHubat commit 6fbd79f

Compare with similar skills

Sc Multi Count 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.

Sc Multi Count compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Sc Multi Count this skillTianGzlab/OmicsClaw161—~1.2kAutomated safety check: PassMIT
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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 Sc Multi Count

What does Sc Multi Count do?

Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels. Sc Multi Count is an agent skill from TianGzlab/OmicsClaw. Load when merging multiple single-sample scRNA-seq count matrices (one per sample-from-sc-count) into a single downstream-ready AnnData with sample labels.

When should I use Sc Multi Count?

Sc Multi Count fits situations like: tasks that involve Bioinformatics.

How do I install Sc Multi Count in Claude Code?

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

How do I install Sc Multi Count in Codex?

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

Can I use Sc Multi Count 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 sc-multi-count -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/sc-multi-count, .gemini/skills/sc-multi-count, .github/skills/sc-multi-count and .opencode/skills/sc-multi-count in your project.

What does Sc Multi Count need to run?

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

Does Sc Multi Count 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 Sc Multi Count 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 Sc Multi Count use?

Sc Multi Count 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 Sc Multi Count use?

About 1.2k tokens (SKILL.md is roughly 4.7k 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 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Sc Multi Count?

Skills that share tags, products or a category with Sc Multi Count: 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 Sc Multi Count?

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.