agentmods.dev

sc-preprocessing

sc-preprocessing is a skill for Claude Code, Codex from TianGzlab/OmicsClaw. It costs 58 tokens per session (1,527 once invoked), scanned A, original, Apache-2.0.

A tool for the standard early processing of quality-controlled single-cell RNA data: normalisation, selection of highly variable genes, and principal component analysis (PCA). PCA is a way to reduce many gene measurements to a smaller set of useful patterns.

In plain words
What is it for?
Turning filtered AnnData into a PCA-ready dataset with normalised values, variable-gene results, and embeddings.
Why use it?
It prepares cleaned data for later clustering or batch integration while stopping before those downstream analyses.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 160repo +1 1mo ago A scan SkillSpector: warn 58 tokens original Apache-2.0

Good fit Turning filtered AnnData into a PCA-ready dataset with normalised values, variable-gene results, and embeddings.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tiangzlab/omicsclaw/sc-preprocessing
View source ↗ TianGzlab/OmicsClaw tiangzlab.github.io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TianGzlab/OmicsClaw --skill sc-preprocessing
Clone the repo
git clone --depth 1 https://github.com/TianGzlab/OmicsClaw

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for sc-preprocessing

README.md
[![agentmods](https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-preprocessing/github.svg)](https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-preprocessing)
Your own site
<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-preprocessing"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-preprocessing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for sc-preprocessing

Your own site · 80×15
<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-preprocessing"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-preprocessing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,527 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Rogue Agent · line 3
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00058 $0.01527
Opus 5 $0.00029 $0.00763
Sonnet 5 $0.00012 $0.00305
Haiku 4.5 $0.00006 $0.00153

Measured 5d ago against content hash 0c13b198f5df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

sc-preprocessing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 4 executable files (sc_preprocess.py, tests/__init__.py, tests/test_sc_preprocess_methods.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/singlecell/scrna/sc-preprocessing/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sc-preprocessing

When to use

The user has a filtered, QC-annotated AnnData and wants the standard "normalise → HVG → PCA" pipeline before clustering or batch integration. Four interchangeable backends are available: scanpy (default; CP10k log + HVG seurat flavour), seurat (R-backed LogNormalize / CLR / RC), sctransform (R-backed regularised NB), and pearson_residuals (raw-count HVG selection plus Pearson residual transformation). The skill stops at PCA — UMAP / clustering live in sc-clustering, multi-sample correction in sc-batch-integration.

Inputs & Outputs

Inputs

  • Modalities: scrna
  • File types: .h5ad

Outputs

  • tables/X_norm.csv
  • tables/cell_metadata.csv
  • tables/cluster_summary.csv
  • tables/embedding_points.csv
  • tables/gene_expression.csv
  • tables/hvg.csv
  • tables/hvg_summary.csv
  • tables/obs.csv
  • tables/pca.csv
  • tables/pca_embedding.csv
  • tables/pca_variance_ratio.csv
  • tables/preprocess_summary.csv
  • tables/qc_metrics_per_cell.csv
  • figures/highly_variable_genes.png
  • figures/pca_variance.png
  • figures/qc_violin.png
  • figures/r_hvg_violin.png
  • analysis_summary.txt
  • info.json
  • processed.h5ad
  • report.md
  • result.json
  • Processed AnnData (saves_h5ad) — adds obsm: X_pca; var: highly_variable; layers: counts
  • AnnData processing state after success: preprocessed

Flow

  1. Load AnnData; infer species; canonicalise gene-name / expression layout via the shared single-cell standardiser.
  2. Reuse existing QC if n_genes_by_counts / total_counts / pct_counts_mt are present in obs; otherwise compute them.
  3. Apply shared filtering (--min-genes, --min-cells, --max-mt-pct); drop doublets when predicted_doublet / doublet_score columns are present (opt out via --no-remove-doublets).
  4. Run the chosen normalisation backend (scanpy / seurat / sctransform / pearson_residuals).
  5. Select HVGs (--n-top-hvg) and compute PCA (--n-pcs).
  6. Save processed.h5ad, tables, figures, report.md, result.json.

Read the full file on GitHub · 127 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 127 lines · 58 tokens per session scan A 0c13b198f5df

Subscribe to this mod's changes

sc-preprocessing is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 58 tokens to every session and 1,527 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Scientificbioinformaticshvgknowledge-graphnormalizationpcapearson_residualspreprocessingscanpyscrnasctransformseuratsinglecell
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