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 starsgit 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/stars)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/stars"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/stars/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/stars"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/stars.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 | $0.00024 | $0.00435 |
| Opus 5 | $0.00012 | $0.00217 |
| Sonnet 5 | $0.00005 | $0.00087 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
stars 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 9d 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
stars Package
Spatiotemporal arrays (raster/vector data cubes).
Read Data
library(stars)
# Single file
r <- read_stars("file.tif")
# Multiple files (time series)
files <- list.files(pattern = "*.tif")
r <- read_stars(files, along = "time")
# NetCDF
nc <- read_stars("file.nc")
Create
# From matrix
m <- matrix(1:20, 4, 5)
s <- st_as_stars(m)
# With dimensions
s <- st_as_stars(list(values = m),
dimensions = st_dimensions(
x = 1:4,
y = 1:5
)
)
Dimensions
# View dimensions
st_dimensions(r)
# Set dimension values
r <- st_set_dimensions(r, "time", values = dates)
# Rename dimensions
r <- setNames(r, "temperature")
Operations
# Subset
r[, 1:10, 1:10]
r[, , , 1:5] # First 5 time steps
# Aggregate
r_agg <- st_apply(r, c("x", "y"), mean)
# Warp (reproject)
r_warp <- st_warp(r, crs = 4326)
# Crop
r_crop <- st_crop(r, bbox)
With sf
library(sf)
# Extract by polygons
vals <- aggregate(r, polygons, FUN = mean)
# Rasterize
r <- st_rasterize(sf_obj)
Plot
plot(r)
# With ggplot2
library(ggplot2)
ggplot() +
geom_stars(data = r) +
scale_fill_viridis_c()
Write
write_stars(r, "output.tif")
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.
- 9d ago First seen · 101 lines · 24 tokens per session scan A 81bdd88107cc
stars is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 6mo ago), licensed MIT. It adds 24 tokens to every session and 435 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 2026-09-03.
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