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.
npx agentmods add skills/tiangzlab/omicsclaw/scatac-preprocessingnpx skills add TianGzlab/OmicsClaw --skill scatac-preprocessinggit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote 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.
[](https://agentmods.dev/skills/tiangzlab/omicsclaw/scatac-preprocessing)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/scatac-preprocessing"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/scatac-preprocessing.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00063 | $0.01554 |
| Opus 5 | $0.00032 | $0.00777 |
| Sonnet 5 | $0.00013 | $0.00311 |
| Haiku 4.5 | $0.00006 | $0.00155 |
Grade A, and why
scatac-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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
scatac-preprocessing
When to use
The user has a peak × cell scATAC AnnData (raw-count-like accessibility
matrix in .X) and wants the standard "filter → TF-IDF → LSI → graph →
UMAP → Leiden" pipeline in one shot. Currently a single backend:
tfidf_lsi (Signac-style). The skill stops at clustered UMAP — no
fragment QC, no peak calling, no motif / gene-activity scoring, no
multi-sample integration. For scRNA preprocessing use sc-preprocessing.
Inputs & Outputs
Inputs
- Input kinds:
file,directory - Modalities: scatac
- File types:
.h5ad,.h5,.loom,.csv,.tsv
Outputs
tables/cell_metadata.csvtables/cluster_summary.csvtables/lsi_variance_ratio.csvtables/peak_summary.csvtables/preprocess_summary.csvtables/qc_metrics_per_cell.csvtables/umap_points.csvfigures/clustering_comparison.pngfigures/feature_umap.pngfigures/lsi_variance.pngfigures/pca_loadings.pngfigures/pca_scatter.pngfigures/pca_variance.pngfigures/qc_violin.pngfigures/top_accessible_peaks.pnganalysis_summary.txtprocessed.h5adreport.mdresult.json- Processed AnnData (
saves_h5ad) — addsobs:leiden;obsm:X_lsi,X_umap;layers:counts - AnnData processing state after success:
preprocessed
Flow
- Load the peak × cell input via the shared
smart_load(AnnData / 10x H5 / loom / CSV / 10x dir). - Validate
.Xis present, non-empty, non-negative. - Compute per-cell
n_peaks_by_counts/total_counts; filter cells by--min-peaksand peaks by--min-cells. - Retain the globally most accessible peaks up to
--n-top-peaks. - Run Signac-style TF-IDF (
--tfidf-scale-factor); truncated-SVD LSI to--n-lsicomponents. - Build neighbour graph (
--n-neighbors), UMAP, Leiden (--leiden-resolution). - Save
processed.h5ad, tables, figures,report.md,result.json.
What ships with it
7 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.
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.
- yesterday First seen · 124 lines · 63 tokens per session scan A b73ed231996e
scatac-preprocessing is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 63 tokens to every session and 1,554 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.
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