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 terragit 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/terra)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/terra"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/terra/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/terra"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/terra.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 | $0.00022 | $0.00441 |
| Opus 5 | $0.00011 | $0.00220 |
| Sonnet 5 | $0.00004 | $0.00088 |
| Haiku 4.5 | $0.00002 | $0.00044 |
Grade A, and why
terra 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
terra Package
Spatial data analysis (raster and vector).
Raster Data
library(terra)
# Read raster
r <- rast("file.tif")
# Create raster
r <- rast(nrows = 100, ncols = 100, xmin = 0, xmax = 10, ymin = 0, ymax = 10)
values(r) <- runif(ncell(r))
# Multi-layer
r <- rast(c("band1.tif", "band2.tif", "band3.tif"))
Raster Operations
# Basic info
dim(r)
res(r)
ext(r)
crs(r)
# Algebra
r2 <- r * 2
r3 <- r + r2
r4 <- sqrt(r)
# Aggregate/Disaggregate
r_agg <- aggregate(r, fact = 2, fun = mean)
r_dis <- disagg(r, fact = 2)
# Resample
r_resamp <- resample(r, template_raster)
# Crop/Mask
r_crop <- crop(r, extent)
r_mask <- mask(r, polygon)
Vector Data
# Read vector
v <- vect("file.shp")
v <- vect("file.gpkg")
# Create from coordinates
pts <- vect(cbind(x, y), crs = "EPSG:4326")
# From sf
v <- vect(sf_object)
sf_obj <- st_as_sf(v)
Vector Operations
# Buffer
v_buf <- buffer(v, width = 1000)
# Intersect
v_int <- intersect(v1, v2)
# Union
v_union <- union(v1, v2)
# Extract raster values
vals <- extract(r, v)
Write
writeRaster(r, "output.tif")
writeVector(v, "output.shp")
Plot
plot(r)
plot(v, add = TRUE)
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 · 96 lines · 22 tokens per session scan A 4ac964aae9f9
terra is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 6mo ago), licensed MIT. It adds 22 tokens to every session and 441 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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