dbplyr

dbplyr is a skill for Claude Code, Codex from LeoLin990405/r-analytics-skill. It costs 27 tokens per session (376 once invoked), scanned A, original, MIT.

An R package that lets dplyr data-manipulation commands work with database tables. Instead of running immediately, the commands are translated into SQL and executed by the database when needed.

In plain words
What is it for?
Use it to filter, group, summarize, sort, rank, and join database tables, inspect the generated SQL, create computed tables, and copy local data into a database.
Why use it?
It lets you use familiar R-style data transformations on tables that may be too large or inconvenient to load into memory.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to filter, group, summarize, sort, rank, and join database tables, inspect the generated SQL, create computed tables, and copy local data into a database.

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Install with agentmods
npx agentmods add skills/leolin990405/r-analytics-skill/dbplyr
Install

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.

Any agent
npx skills add LeoLin990405/r-analytics-skill --skill dbplyr
Clone the repo
git clone --depth 1 https://github.com/LeoLin990405/r-analytics-skill

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for dbplyr

README.md
[![agentmods](https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/dbplyr/github.svg)](https://agentmods.dev/skills/leolin990405/r-analytics-skill/dbplyr)
Your own site
<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/dbplyr"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/dbplyr/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.

agentmods 80×15 button for dbplyr

Your own site · 80×15
<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/dbplyr"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/dbplyr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 376 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00027 $0.00376
Opus 5 $0.00014 $0.00188
Sonnet 5 $0.00005 $0.00075
Haiku 4.5 $0.00003 $0.00038

Measured 9d ago against content hash b13e760f9df4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

dbplyr 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.

sub-skills/r-data/r-data-database/dbplyr/SKILL.md · 81 lines

What it actually says

dbplyr Package

dplyr backend for databases with lazy evaluation.

Connect and Use

library(dplyr)
library(dbplyr)
library(DBI)

con <- dbConnect(RSQLite::SQLite(), "database.db")

# Reference table (lazy)
tbl_flights <- tbl(con, "flights")

# dplyr verbs (translated to SQL)
result <- tbl_flights %>%
  filter(year == 2023) %>%
  group_by(carrier) %>%
  summarise(
    n = n(),
    avg_delay = mean(arr_delay, na.rm = TRUE)
  ) %>%
  arrange(desc(n))

# View SQL
show_query(result)

# Execute and collect
df <- collect(result)

SQL Translation

# See generated SQL
tbl_flights %>%
  filter(distance > 1000) %>%
  select(carrier, flight, distance) %>%
  show_query()

# Custom SQL
tbl(con, sql("SELECT * FROM flights WHERE year = 2023"))

Window Functions

tbl_flights %>%
  group_by(carrier) %>%
  mutate(
    rank = row_number(),
    pct = percent_rank()
  ) %>%
  show_query()

Compute/Copy

# Create temp table from query
tbl_flights %>%
  filter(month == 1) %>%
  compute("jan_flights")

# Copy local df to database
copy_to(con, local_df, "new_table")

Disconnect

dbDisconnect(con)
Changes

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.

  1. 9d ago First seen · 81 lines · 27 tokens per session scan A b13e760f9df4

Subscribe to this mod's changes

dbplyr is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 376 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 2026-08-31.

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