Find agent skills by outcome

ifelse(x > 0

pos

df[df$value > 10

name] # filter + select

df[1:5

] # first 5 rows

df[

c(name

x[c(TRUE

FALSE)] # by logical

df[df$value > 15

] # filter rows

name = c(a

b

value = c(10.5

20.3

m[

2] # second column

lst <- list(name = ali

scores = c(90

m[1

] # first row

m <- matrix(1:6

nrow = 2

f <- factor(c(low

med

z <- c(TRUE

FALSE

x <- c(1

2

y <- c(a

b

A comprehensive reference for base R programming — covering data structures

control flow

base-R

description: Provides base R programming guidance covering data structures

data wrangling

When you ask for help

the agent responds with:

- Separate facts vs recommendations: Label “documented behavior” versus “recommended approach

” especially for residency and retention.

- “What exactly changes with EU data residency

and what must we verify for auditors?”

- Verification-first for compliance claims: Provide checklists (stream enabled

destination retention policy

- No guessing: If a fact depends on tenant configuration

licensing