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-drug-responsegit 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-drug-response)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-drug-response"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-drug-response/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-drug-response"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-drug-response.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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.
- medium Rogue Agent · line 81 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00080 | $0.01784 |
| Opus 5 | $0.00040 | $0.00892 |
| Sonnet 5 | $0.00016 | $0.00357 |
| Haiku 4.5 | $0.00008 | $0.00178 |
Grade A, and why
sc-drug-response 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sc-drug-response
When to use
The user has a clustered / labelled scRNA AnnData with HGNC-symbol gene names and wants per-cluster drug sensitivity rankings. Two methods:
simple_correlation(default) — built-in lightweight scorer: correlates per-cluster mean expression with drug-target signatures from_BUILTIN_DRUG_TARGETS. No external models, no CaDRReS install.cadrres— runs CaDRReS-Sc against pretrained GDSC or PRISM models. Requires the CaDRReS-Sc script directory plus model files locally (cache at~/.cache/omicsclaw/cadrres/<drug-db>/).
For genetic perturbation predictions (KO / KD / overexpression on
unperturbed data) use sc-in-silico-perturbation. For real Perturb-seq
classification use sc-perturb.
Inputs & Outputs
Inputs
- Modalities: scrna
- File types:
.h5ad - Requires a preprocessed AnnData (
Xnormalised, PCA/neighbours present)
Outputs
tables/IC50_prediction.csvtables/PRISM_prediction.csvtables/cell_metadata.csvtables/drug_rankings.csvtables/masked_drugs.csvfigures/drug_cluster_heatmap.pngfigures/drug_sensitivity_umap.pngfigures/top_drugs_bar.pnganalysis_summary.txtprocessed.h5adreport.mdresult.json- Processed AnnData (
saves_h5ad) — addsobs:drug_score_<drug>
Flow
- Load AnnData; resolve
--cluster-key(auto-pick fromleiden/louvain/cell_type/ first categorical if unset). - Preflight:
cluster_keyexists + has ≥ 2 groups (warn-only on < 2); gene-name overlap with drug targets. - For
cadrres: validate--model-dirhas the GDSC / PRISM files + locate the CaDRReS-Sc script directory; run viaDrug_Responsewrapper. - For
simple_correlation: compute per-cluster expression means, correlate against_BUILTIN_DRUG_TARGETS, rank drugs per cluster. - Detect degenerate output (empty rankings / all-NaN scores) → print multi-action fix message; do NOT raise.
- Render bar / heatmap / UMAP figures, write
tables/drug_rankings.csv, savereport.md,result.json.
What ships with it
6 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 · 120 lines · 80 tokens per session scan A 3f6ea49d4098
sc-drug-response is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 1,784 once invoked, about $0.0004 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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