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 genomicrangesgit 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/genomicranges)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/genomicranges"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/genomicranges/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/genomicranges"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/genomicranges.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 | $0.00021 | $0.00502 |
| Opus 5.5 | $0.00008 | $0.00201 |
| Sonnet 5.5 | $0.00004 | $0.00100 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
GenomicRanges scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
GenomicRanges Package
Representation and manipulation of genomic intervals.
GRanges Object
library(GenomicRanges)
# Create GRanges
gr <- GRanges(
seqnames = c("chr1", "chr1", "chr2"),
ranges = IRanges(start = c(100, 200, 150), end = c(150, 250, 200)),
strand = c("+", "-", "+"),
score = c(1.5, 2.0, 3.0)
)
# From data frame
gr <- makeGRangesFromDataFrame(df,
seqnames.field = "chr",
start.field = "start",
end.field = "end"
)
Accessors
seqnames(gr)
start(gr)
end(gr)
width(gr)
strand(gr)
ranges(gr)
mcols(gr) # Metadata columns
gr$score # Access metadata
Subsetting
gr[1:5]
gr[seqnames(gr) == "chr1"]
gr[strand(gr) == "+"]
gr[gr$score > 2]
Operations
# Shift
shift(gr, 100)
# Resize
resize(gr, width = 500, fix = "start")
# Flank
flank(gr, width = 100, start = TRUE)
# Promoters
promoters(gr, upstream = 2000, downstream = 200)
# Reduce (merge overlapping)
reduce(gr)
# Disjoin
disjoin(gr)
Overlaps
# Find overlaps
hits <- findOverlaps(query, subject)
# Subset by overlap
subsetByOverlaps(gr1, gr2)
# Count overlaps
countOverlaps(gr1, gr2)
# Overlap operations
intersect(gr1, gr2)
union(gr1, gr2)
setdiff(gr1, gr2)
GRangesList
grl <- GRangesList(gene1 = gr1, gene2 = gr2)
grl[[1]]
unlist(grl)
Import/Export
library(rtracklayer)
gr <- import("file.bed")
export(gr, "output.bed")
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.
- 1mo ago First seen · 108 lines · 21 tokens per session scan A b3379721d024
GenomicRanges is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 7mo ago), licensed MIT. It adds 21 tokens to every session and 502 once invoked, about $0.0001 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 2026-08-31.
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