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 skills add TianGzlab/OmicsClaw --skill sc-countgit 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/sc-count)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-count"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-count/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.
<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-count"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-count.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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.
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 5.1 | $0.00062 | $0.01453 |
| Opus 5 | $0.00031 | $0.00727 |
| Sonnet 5 | $0.00012 | $0.00291 |
| Haiku 4.5 | $0.00006 | $0.00145 |
Grade A, and why
sc-count 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.
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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sc-count
When to use
The user has FASTQ files (or pre-existing tool output directories) and
wants per-cell counts in OmicsClaw's canonical AnnData contract. Four
backends share one CLI: cellranger, starsolo, simpleaf,
kb-python. When passed an already-counted directory the skill
re-canonicalises rather than re-counts. Pairs with sc-fastq-qc
upstream (read QC) and sc-multi-count downstream (merging multiple
samples).
Inputs & Outputs
Inputs
- Input kinds:
file,directory - Modalities: scrna
- File types:
.fastq,.fq,.h5ad - FASTQ structure: valid first record;
pairedlayout - Directory layouts (any):
paired-fastq,tenx-matrix,cellranger-output,starsolo-output,pseudoalign-output
Outputs
tables/Summary.csvtables/backend_summary.csvtables/barcode_metrics.csvtables/barcodes.tsvtables/cell_metadata.csvtables/count_summary.csvtables/features.tsvtables/genes.tsvtables/metrics_summary.csvtables/simpleaf_t2g.tsvfigures/barcode_rank.pngfigures/count_complexity_scatter.pngfigures/count_distributions.png3M-february-2018.txt737K-august-2016.txtAligned.sortedByCoord.out.bamanalysis_summary.txtcells_x_genes.barcodes.txtcells_x_genes.genes.txtmultiqc_report.htmlpossorted_genome_bam.bamprocessed.h5adquants_mat_cols.txtquants_mat_rows.txtsimpleaf_index.jsonstandardized_input.h5adweb_summary.htmlreport.mdresult.json- Processed AnnData (
saves_h5ad)
Flow
- Resolve
--input; if it's an existing CellRanger / STARsolo / SimpleAF / kb-python output dir, re-canonicalise instead of running the backend. - Otherwise validate backend prerequisites (chemistry, reference, t2g for kb-python, whitelist for STARsolo).
- Run the chosen backend against the FASTQ (and
--read2if explicit). - Load the resulting matrix into AnnData; canonicalise (
layers["counts"],adata.raw, gene-name harmonisation). - Render barcode-rank + count-distribution figures.
- Emit
processed.h5ad+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.
- 5d ago First seen · 130 lines · 62 tokens per session scan A b2ff6fdd602a
sc-count is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,453 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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