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/readrnpx skills add LeoLin990405/r-analytics-skill --skill readrgit 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/readr)<a href="https://agentmods.dev/skills/leolin990405/r-analytics-skill/readr"><img src="https://agentmods.dev/badge/skills/leolin990405/r-analytics-skill/readr.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 5.1 | $0.00025 | $0.00857 |
| Opus 5 | $0.00013 | $0.00428 |
| Sonnet 5 | $0.00005 | $0.00171 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
readr 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 6d 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 — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
readr
Fast rectangular data reading.
Read Functions
library(readr)
# CSV
df <- read_csv("file.csv")
df <- read_csv("file.csv", col_names = FALSE)
df <- read_csv("file.csv", skip = 2)
df <- read_csv("file.csv", n_max = 1000)
# TSV
df <- read_tsv("file.tsv")
# Delimited
df <- read_delim("file.txt", delim = "|")
# Fixed width
df <- read_fwf("file.txt", fwf_widths(c(10, 5, 8)))
df <- read_fwf("file.txt", fwf_positions(c(1, 11, 16), c(10, 15, 23)))
# Lines
lines <- read_lines("file.txt")
# Whole file
text <- read_file("file.txt")
Column Specification
# Explicit types
df <- read_csv("file.csv", col_types = cols(
id = col_integer(),
name = col_character(),
value = col_double(),
date = col_date(format = "%Y-%m-%d"),
flag = col_logical()
))
# Column types
col_logical()
col_integer()
col_double()
col_character()
col_factor(levels = c("A", "B", "C"))
col_date(format = "")
col_datetime(format = "")
col_time(format = "")
col_number()
col_skip()
col_guess()
# Shorthand
df <- read_csv("file.csv", col_types = "icdDl")
# i = integer, c = character, d = double, D = date, l = logical
# n = number, _ = skip, ? = guess
Options
df <- read_csv("file.csv",
# Column names
col_names = TRUE,
col_names = c("a", "b", "c"),
# Skip/limit
skip = 0,
n_max = Inf,
skip_empty_rows = TRUE,
# Missing values
na = c("", "NA", "NULL", "-999"),
# Locale
locale = locale(
encoding = "UTF-8",
decimal_mark = ".",
grouping_mark = ",",
date_format = "%Y-%m-%d",
tz = "UTC"
),
# Quoting
quote = "\"",
# Comments
comment = "#",
# Trimming
trim_ws = TRUE,
# Progress
progress = TRUE
)
Write Functions
# CSV
write_csv(df, "output.csv")
write_csv(df, "output.csv", na = "")
write_csv(df, "output.csv", append = TRUE)
# TSV
write_tsv(df, "output.tsv")
# Delimited
write_delim(df, "output.txt", delim = "|")
# Excel-friendly CSV
write_excel_csv(df, "output.csv")
# Lines
write_lines(lines, "output.txt")
# File
write_file(text, "output.txt")
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.
- 6d ago First seen · 158 lines · 25 tokens per session scan A 1794dbd07dfd
readr is a skill published in the GitHub repository LeoLin990405/r-analytics-skill (5 stars, last pushed 5mo ago), licensed MIT. It adds 25 tokens to every session and 857 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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