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-degit 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-de)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/bulkrna-de"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-de/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-de"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-de.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 | $0.00054 | $0.00815 |
| Opus 5.5 | $0.00022 | $0.00326 |
| Sonnet 5.5 | $0.00011 | $0.00163 |
| Haiku 4.5 | $0.00005 | $0.00081 |
Grade A, and why
bulkrna-de 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 17d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bulk differential expression
Purpose
Compare two prefix-selected groups in a raw count matrix. The default backend is R DESeq2; --method ttest selects Welch tests. The R bridge applies apeglm or ashr shrinkage when installed, otherwise raw estimates. This is not a single-cell or splicing analysis.
Inputs & Outputs
CLI input is a gene-first CSV. The library takes a gene-indexed DataFrame. Both require nonnegative integer counts. Outputs include tables/de_results.csv, tables/de_significant.csv, four diagnostic figures, report.md and result.json; DESeq2 intermediate tables are backend-dependent.
API
differential_expression(counts, *, method='deseq2', control_prefix='ctrl', treat_prefix='treat', padj_cutoff=0.05, lfc_cutoff=1.0, min_count=10)
Compare treatment against control without changing the count matrix.
:param counts: Gene-indexed DataFrame of nonnegative integer raw counts. :param method: CLI default deseq2 (R); ttest selects Welch tests. :param control_prefix: CLI default ctrl selects control columns. :param treat_prefix: CLI default treat selects treatment columns. :param padj_cutoff: CLI default 0.05; significance requires a smaller adjusted p. :param lfc_cutoff: CLI default 1.0; absolute log2 effect must exceed it. :param min_count: Legacy filtering default 10 for total counts across selected samples. :returns: DE DataFrame with effect estimates, p values and run diagnostics in attrs. :raises ValueError: Counts, method, groups or thresholds are invalid. :raises ImportError: R DESeq2 is missing; use install_skill_deps for DESeq2.
run_info(result, *, keep=True)
Read filtering, group and executed-method diagnostics.
:param result: DataFrame returned by differential_expression. :param keep: Default True; False removes diagnostics from attrs. :returns: Diagnostic dictionary, empty after removal.
volcano_figure(result)
Plot reported log2 effects and adjusted significance.
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.
- _api.py 3.4 KB runs code
- bulkrna_de.py 11 KB runs code
- examples/example_step.py 552 B runs code
- references/methodology.md 1.0 KB
- references/output_contract.md 1.6 KB
- references/parameters.md 294 B
- tests/__init__.py 0 B runs code
- tests/test_api.py 1.9 KB runs code
- tests/test_bulkrna_de.py 1.9 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.
- 17d ago Changed · -17 lines 7bfb81708985
- 1mo ago First seen · 96 lines · 54 tokens per session scan A a603e0e81588
bulkrna-de is a skill published in the GitHub repository TianGzlab/OmicsClaw (161 stars, last pushed 17d ago), licensed Apache-2.0. It adds 54 tokens to every session and 815 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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