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-spatial-vectorgit 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-spatial-vector)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-spatial-vector"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-spatial-vector/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-spatial-vector"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-spatial-vector.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 | $0.00028 | $0.00490 |
| Opus 5 | $0.00014 | $0.00245 |
| Sonnet 5 | $0.00006 | $0.00098 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
r-spatial-vector 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
R Vector Spatial Data
Points, lines, and polygons.
sf (Simple Features)
library(sf)
# Read/write
shp <- st_read("file.shp")
geojson <- st_read("file.geojson")
st_write(shp, "output.gpkg")
# Create geometries
pt <- st_point(c(0, 0))
line <- st_linestring(matrix(c(0,0, 1,1, 2,0), ncol = 2, byrow = TRUE))
poly <- st_polygon(list(matrix(c(0,0, 1,0, 1,1, 0,1, 0,0), ncol = 2, byrow = TRUE)))
# Create sf object
df <- data.frame(id = 1:3, name = c("A", "B", "C"))
geom <- st_sfc(pt1, pt2, pt3, crs = 4326)
sf_obj <- st_sf(df, geometry = geom)
# CRS operations
st_crs(shp)
st_transform(shp, 4326)
st_set_crs(shp, 4326)
# Geometric operations
st_buffer(shp, dist = 100)
st_intersection(shp1, shp2)
st_union(shp)
st_difference(shp1, shp2)
st_centroid(shp)
st_area(shp)
st_length(lines)
st_distance(shp1, shp2)
# Spatial predicates
st_intersects(shp1, shp2)
st_contains(shp1, shp2)
st_within(shp1, shp2)
st_touches(shp1, shp2)
# Spatial joins
st_join(points, polygons)
st_filter(points, polygon)
terra (Vectors)
library(terra)
# Read/write
v <- vect("file.shp")
writeVector(v, "output.gpkg")
# Create
pts <- vect(cbind(x, y), crs = "EPSG:4326")
# Operations
buffer(v, width = 100)
intersect(v1, v2)
union(v1, v2)
aggregate(v, by = "field")
What ships with it
4 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.
- 9d ago First seen · 74 lines · 28 tokens per session scan A 3b17da554b30
r-spatial-vector is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 6mo ago), licensed MIT. It adds 28 tokens to every session and 490 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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