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 agentmods add skills/leolin990405/r-analytics-skill/r-data-databasenpx skills add LeoLin990405/r-analytics-skill --skill r-data-databasegit 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-data-database)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/r-data-database"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/r-data-database.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.01070 |
| Opus 5 | $0.00020 | $0.00535 |
| Sonnet 5 | $0.00008 | $0.00214 |
| Haiku 4.5 | $0.00004 | $0.00107 |
Grade A, and why
r-data-database 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
R Database Connections
SQL and NoSQL database access from R.
DBI (Common Interface)
library(DBI)
# Connect
con <- dbConnect(RSQLite::SQLite(), "database.db")
con <- dbConnect(RPostgres::Postgres(),
host = "localhost", dbname = "mydb",
user = "user", password = "pass"
)
# Query
result <- dbGetQuery(con, "SELECT * FROM table WHERE x > 10")
# Execute (no return)
dbExecute(con, "INSERT INTO table VALUES (1, 'a')")
dbExecute(con, "UPDATE table SET x = 10 WHERE id = 1")
# Parameterized queries (safe)
dbGetQuery(con, "SELECT * FROM table WHERE id = ?", params = list(123))
# Tables
dbListTables(con)
dbExistsTable(con, "mytable")
dbWriteTable(con, "newtable", df)
dbReadTable(con, "mytable")
dbRemoveTable(con, "mytable")
# Disconnect
dbDisconnect(con)
dbplyr (dplyr for databases)
library(dplyr)
library(dbplyr)
con <- dbConnect(RSQLite::SQLite(), "database.db")
# Lazy table reference
tbl_db <- tbl(con, "mytable")
# dplyr operations (translated to SQL)
result <- tbl_db %>%
filter(x > 10) %>%
select(a, b, c) %>%
group_by(category) %>%
summarise(mean = mean(value)) %>%
collect() # Execute and bring to R
# View SQL
tbl_db %>% filter(x > 10) %>% show_query()
# Copy local data to database
copy_to(con, df, "temp_table", temporary = TRUE)
SQLite
library(RSQLite)
con <- dbConnect(SQLite(), "mydb.sqlite")
# In-memory database
con <- dbConnect(SQLite(), ":memory:")
dbWriteTable(con, "mtcars", mtcars)
dbGetQuery(con, "SELECT * FROM mtcars WHERE mpg > 20")
dbDisconnect(con)
PostgreSQL
library(RPostgres)
con <- dbConnect(Postgres(),
host = "localhost",
port = 5432,
dbname = "mydb",
user = "user",
password = "password"
)
# With connection string
con <- dbConnect(Postgres(),
"postgresql://user:pass@host:5432/dbname"
)
MySQL/MariaDB
library(RMariaDB)
con <- dbConnect(MariaDB(),
host = "localhost",
dbname = "mydb",
user = "user",
password = "password"
)
ODBC (Universal)
What ships with it
7 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.
- 4d ago First seen · 204 lines · 40 tokens per session scan A 9ec5df3d5d32
r-data-database is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 1,070 once invoked, about $0.0002 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 2026-08-31.
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