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 LeoLin990405/r-analytics-skill --skill r-bio-rnaseqgit clone --depth 1 https://github.com/LeoLin990405/r-analytics-skillWrote 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/leolin990405/r-analytics-skill/r-bio-rnaseq)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-bio-rnaseq"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-bio-rnaseq/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/leolin990405/r-analytics-skill/r-bio-rnaseq"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-bio-rnaseq.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00029 | $0.00486 |
| Opus 5 | $0.00015 | $0.00243 |
| Sonnet 5 | $0.00006 | $0.00097 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
r-bio-rnaseq scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
R RNA-seq Analysis
Differential expression analysis.
DESeq2
library(DESeq2)
# Create object
dds <- DESeqDataSetFromMatrix(
countData = counts,
colData = sample_info,
design = ~ condition
)
# Filter low counts
keep <- rowSums(counts(dds)) >= 10
dds <- dds[keep,]
# Run DESeq
dds <- DESeq(dds)
# Results
res <- results(dds, contrast = c("condition", "treated", "control"))
res <- results(dds, alpha = 0.05)
summary(res)
# Significant genes
sig <- res[which(res$padj < 0.05), ]
sig_up <- sig[sig$log2FoldChange > 1, ]
sig_down <- sig[sig$log2FoldChange < -1, ]
# Visualization
plotMA(res)
plotPCA(vst(dds), intgroup = "condition")
edgeR
library(edgeR)
# Create object
y <- DGEList(counts = counts, group = group)
# Filter
keep <- filterByExpr(y)
y <- y[keep, , keep.lib.sizes = FALSE]
# Normalize
y <- calcNormFactors(y)
# Dispersion
y <- estimateDisp(y)
# Test
et <- exactTest(y)
topTags(et)
# GLM approach
design <- model.matrix(~ group)
fit <- glmQLFit(y, design)
qlf <- glmQLFTest(fit, coef = 2)
topTags(qlf)
Gene Set Enrichment
library(clusterProfiler)
# GO enrichment
ego <- enrichGO(gene = sig_genes, OrgDb = org.Hs.eg.db, keyType = "ENSEMBL", ont = "BP")
dotplot(ego)
# KEGG
ekegg <- enrichKEGG(gene = entrez_ids, organism = "hsa")
# GSEA
gse <- gseGO(geneList = ranked_genes, OrgDb = org.Hs.eg.db, ont = "BP")
What ships with it
3 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.
- 11d ago First seen · 88 lines · 29 tokens per session scan A 66b06d6768ad
r-bio-rnaseq is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 29 tokens to every session and 486 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.
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