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 bulkrna-enrichmentgit 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/bulkrna-enrichment)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/bulkrna-enrichment"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-enrichment/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/bulkrna-enrichment"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-enrichment.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 | $0.00059 | $0.00811 |
| Opus 5.5 | $0.00024 | $0.00324 |
| Sonnet 5.5 | $0.00012 | $0.00162 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
bulkrna-enrichment 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 19d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bulk pathway enrichment
Purpose
Test differential-expression results against explicit pathway gene sets. ORA uses the union of those sets as its background; GSEA ranks all input genes. Gene identifiers must use the same namespace. R adapters are not implemented.
Inputs & Outputs
CLI input is a CSV with gene, log2FoldChange, pvalue, padj; --gene-set-file is a JSON mapping from pathway names to gene lists. The library accepts the table and mapping directly. CLI writes tables/enrichment_results.csv, tables/enrichment_significant.csv, report/result files and method-dependent figures.
API
enrich(de_results, *, gene_sets, method='ora', padj_cutoff=0.05, lfc_cutoff=1.0, random_state=42)
Test pathway enrichment without choosing a reference database.
:param de_results: DataFrame with gene, log2FoldChange, pvalue and padj. :param gene_sets: Nonempty mapping from pathway names to unique gene lists. :param method: CLI default ora; gsea runs GSEApy prerank. :param padj_cutoff: CLI significance threshold, default 0.05. :param lfc_cutoff: Strict absolute fold-change threshold, default 1.0. :param random_state: Local permutation seed, legacy default 42. :returns: Enrichment DataFrame with execution diagnostics in attrs. :raises ValueError: Missing reference, invalid values or unsupported method.
run_info(result, *, keep=True)
Read tested terms, pathway universe and requested/executed methods.
:param result: DataFrame returned by enrich. :param keep: Default True; False removes diagnostic attrs. :returns: Diagnostic dictionary; empty after removal.
enrichment_figure(result)
Plot pathway adjusted significance without saving it.
:param result: Enrichment DataFrame with term and padj columns. :returns: matplotlib Figure. :raises KeyError: Required columns are missing.
Key CLI
python skills/bulkrna/bulkrna-enrichment/bulkrna_enrichment.py --demo --output /tmp/bulkrna-enrichment
python skills/bulkrna/bulkrna-enrichment/bulkrna_enrichment.py --input de.csv --gene-set-file pathways.json --output results/enrichment --method ora
What ships with it
10 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.
- _api.py 3.3 KB runs code
- bulkrna_enrichment.py 14 KB runs code
- examples/example_step.py 705 B runs code
- references/methodology.md 1.1 KB
- references/output_contract.md 1.1 KB
- references/parameters.md 274 B
- tests/__init__.py 0 B runs code
- tests/biomnibench_da12_2.py 14 KB runs code
- tests/test_api.py 1.1 KB runs code
- tests/test_bulkrna_enrichment.py 5.0 KB runs code
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.
- 19d ago Changed · -9 lines 013ac0b8cabe
- 1mo ago First seen · 89 lines · 59 tokens per session scan A 9b53ed45e862
bulkrna-enrichment is a skill published in the GitHub repository TianGzlab/OmicsClaw (161 stars, last pushed 20d ago), licensed Apache-2.0. It adds 59 tokens to every session and 811 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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