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-differential-abundancegit 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-differential-abundance)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-differential-abundance"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-differential-abundance/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-differential-abundance"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-differential-abundance.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 | $0.00068 | $0.01676 |
| Opus 5 | $0.00034 | $0.00838 |
| Sonnet 5 | $0.00014 | $0.00335 |
| Haiku 4.5 | $0.00007 | $0.00168 |
Grade A, and why
sc-differential-abundance 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 6d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sc-differential-abundance
When to use
The user has a multi-sample, multi-condition scRNA AnnData and asks "Did the relative abundance of these cell states change between conditions?" — distinct from per-cell DE. Four methods:
milo(default) — neighbourhood-level DA, replicate-aware (pertpy).sccoda— Bayesian compositional analysis with a reference cell type (pertpy).simple— exploratory proportion screen, no pertpy needed.proportion_test_r— base-R Monte-Carlo permutation; lollipop plots with bootstrap 95% CI.
For per-cell expression changes between conditions, use sc-de.
For ranking what defines a cluster, use sc-markers.
Inputs & Outputs
Inputs
- Modalities: scrna
- File types:
.h5ad - Requires a preprocessed AnnData (
Xnormalised, PCA/neighbours present)
Outputs
tables/cell_meta.csvtables/cell_metadata.csvtables/condition_mean_proportions.csvtables/milo_nhood_results.csvtables/proportion_test_results.csvtables/sample_by_celltype_counts.csvtables/sample_by_celltype_proportions.csvtables/sccoda_effects.csvtables/simple_da_results.csvfigures/milo_logfc_barplot.pngfigures/proportion_test_r_no_results.pngfigures/r_cell_barplot.pngfigures/r_cell_density.pngfigures/r_embedding_discrete.pngfigures/r_proportion_test.pngfigures/sample_celltype_proportions.pngfigures/sccoda_log2fc_barplot.pnganalysis_summary.txtannotated_input.h5adprocessed.h5adreport.mdresult.json- Processed AnnData (
saves_h5ad)
Flow
- Load AnnData; validate
--method,--fdr,--n-neighbors,--prop,--n-permutations. - Run preflight on
--condition-key,--sample-key,--cell-type-key— fail fast on missing columns or under-replication. - Build the universal composition summary (counts / proportions / condition means) and save them.
- Dispatch to the method-specific runner (
run_milo_da/run_sccoda_da/ simple proportion test / R proportion test). - Append method-specific summary fields to
result.json(n_nhoods/n_effect_rows/n_cell_types/n_significant, plusbackendfor milo/sccoda). - Save 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.
- 6d ago First seen · 133 lines · 68 tokens per session scan A ce471cc4d746
sc-differential-abundance is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 68 tokens to every session and 1,676 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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