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 Azealoo/miniAgent --skill pseudobulk_design_helpergit clone --depth 1 https://github.com/Azealoo/miniAgentWrote 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/azealoo/miniagent/pseudobulk_design_helper)<a href="https://agentmods.dev/skills/azealoo/miniagent/pseudobulk_design_helper"><img src="https://agentmods.dev/badge/skills/azealoo/miniagent/pseudobulk_design_helper.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00026 | $0.00474 |
| Opus 5 | $0.00013 | $0.00237 |
| Sonnet 5 | $0.00005 | $0.00095 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
pseudobulk_design_helper 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 7d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 7d ago First seen · 59 lines · 26 tokens per session scan A d1b92d0d1189
pseudobulk_design_helper is a skill published in the GitHub repository Azealoo/miniAgent (2 stars, last pushed 2mo ago), with no licence file. It adds 26 tokens to every session and 474 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
spatial-condition
Load when comparing two or more experimental conditions (treatment vs control) on a multi-sample preprocessed spatial AnnData via PyDESeq2 pseudobulk or Wilcoxon DE — needs obs[conditionkey], obs[samplekey], and cluster labels. Skip when running per-cluster DE on one condition (use spatial-de); comparing two slices…
spatial-de
Load when ranking spatial cluster markers or comparing two spatial groups in spatial transcriptomics. Skip when the data is single-cell (use sc-de); bulk (use bulkrna-de); spatially variable expression discovery (use spatial-genes).
spatial-condition-comparison
Experimental condition comparison using pseudobulk differential expression with proper multi-sample statistics.
sc-de
Load when finding marker genes per cluster or comparing condition expression in single-cell RNA-seq. Skip when the data is bulk (use bulkrna-de); spatial (use spatial-de); cluster-only markers without conditions (use sc-markers).
proteomics-de
Load when computing two-group differential protein abundance (group2 vs group1, log2FC + p-value + BH-adjusted FDR) via Welch t-test, equal-variance t-test, or Mann-Whitney on a wide protein × sample CSV. Skip when you need multi-condition DE (run pairwise contrasts manually); label-based TMT linear-mixed models.
bulkrna-de
Load when comparing gene expression between two conditions in bulk RNA-seq count data. Skip when the data is single-cell (use sc-de); spatial (use spatial-de); you need exon-level alternative splicing (use bulkrna-splicing).