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-language-apigit 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-language-api)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-language-api"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-language-api/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-language-api"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-language-api.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 | $0.00026 | $0.00482 |
| Opus 5 | $0.00013 | $0.00241 |
| Sonnet 5 | $0.00005 | $0.00096 |
| Haiku 4.5 | $0.00003 | $0.00048 |
Grade A, and why
r-language-api scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
R Language Interfaces
Call other programming languages from R.
reticulate (Python)
library(reticulate)
# Use Python
py_run_string("x = 1 + 1")
py$x
# Import modules
np <- import("numpy")
pd <- import("pandas")
# Call Python functions
np$array(c(1, 2, 3))
pd$DataFrame(list(a = 1:3, b = 4:6))
rJava (Java)
library(rJava)
# Initialize JVM
.jinit()
# Create Java objects
str <- .jnew("java/lang/String", "Hello")
# Call methods
.jcall(str, "I", "length")
.jcall(str, "S", "toUpperCase")
V8 (JavaScript)
library(V8)
# Create context
ctx <- v8()
# Run JavaScript
ctx$eval("var x = 1 + 1")
ctx$get("x")
# Call functions
ctx$eval("function add(a, b) { return a + b; }")
ctx$call("add", 1, 2)
Rcpp (C++)
library(Rcpp)
# Inline C++
cppFunction('
int add(int x, int y) {
return x + y;
}
')
add(1, 2)
# Source C++ file
sourceCpp("functions.cpp")
Data Exchange
# R to Python
py$df <- r_to_py(mtcars)
# Python to R
r_df <- py_to_r(py$df)
# Automatic conversion
reticulate::py_config()
Best Practices
# 1. Check availability
reticulate::py_available()
rJava::.jcheck()
# 2. Handle errors
tryCatch({
py_run_string("import nonexistent")
}, error = function(e) {
message("Python error: ", e$message)
})
# 3. Clean up resources
# Java: .jgc()
# V8: ctx$reset()
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.
- 7d ago First seen · 109 lines · 26 tokens per session scan A 7fb5a6a2e39e
r-language-api is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 26 tokens to every session and 482 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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