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 rgdalgit 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/rgdal)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/rgdal"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/rgdal/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/rgdal"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/rgdal.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 | $0.00306 |
| Opus 5 | $0.00014 | $0.00153 |
| Sonnet 5 | $0.00006 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
rgdal 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
rgdal
Bindings for GDAL/OGR (deprecated - use sf or terra).
Note
rgdal was retired in October 2023. Use sf or terra instead.
Migration to sf
# Old rgdal way
library(rgdal)
shp <- readOGR("data.shp")
writeOGR(shp, "output.shp", layer = "data", driver = "ESRI Shapefile")
# New sf way
library(sf)
shp <- st_read("data.shp")
st_write(shp, "output.shp")
Migration to terra
# Old rgdal way
library(rgdal)
raster <- readGDAL("raster.tif")
# New terra way
library(terra)
raster <- rast("raster.tif")
CRS Handling
# Old way
proj4string(sp_obj) <- CRS("+proj=longlat +datum=WGS84")
spTransform(sp_obj, CRS("+proj=utm +zone=10"))
# New sf way
st_crs(sf_obj) <- 4326
st_transform(sf_obj, 32610)
Available Drivers
# In sf
st_drivers()
# In terra
gdal(drivers = 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 · 61 lines · 28 tokens per session scan A bbca251e8d63
rgdal 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 306 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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