Explore

Find agent skills by outcome

19,395 skills indexed with the new KISS metadata standard.

Showing 24 of 19,395Categories: Data, Communication, Productivity, Coding & Debugging
Data
PromptBeginner5 minmarkdownQuality: 28

Ultra-micro Functional Analyst Prompt

Act as a senior functional analyst: work in phases, state all assumptions, preserve existing behaviour, no UML/Gherkin/specs without explicit approval, be direct and analytical.

0
Communication
PromptBeginner5 minmarkdownQuality: 24

Communication: direct

precise

0
Data
PromptBeginner5 minmarkdownQuality: 24

Small Functional Analyst mode

Functional Analyst Mode

0
Productivity
PromptBeginner5 minmarkdownQuality: 24

- Append-only to these files: task.md

implementation-plan.md

0
Data
PromptBeginner5 minmarkdownQuality: 28

Functional Analyst

Act as a Senior Functional Analyst. Your role prioritizes correctness, clarity, traceability, and controlled scope, following UML2, Gherkin, and Agile/Scrum methodologies. Below are your core principl...

0
Data
PromptBeginner5 minmarkdownQuality: 28

Probably the most useful standalone thing here. Source it and run check_data(df) on any data frame t...

NA counts

0
Data
PromptBeginner5 minmarkdownQuality: 24

│ ├── statistics.md # Hypothesis tests

distributions

0
Data
PromptBeginner5 minmarkdownQuality: 24

│ ├── visualization.md # par

layout

0
Data
PromptBeginner5 minmarkdownQuality: 24

│ ├── data-wrangling.md # Subsetting traps

apply family

0
Coding & Debugging
PromptBeginner5 minmarkdownQuality: 28

I'm a political science PhD candidate who uses R regularly but would never call myself an R person....

without ggplot2

0
Data
PromptBeginner5 minmarkdownQuality: 24

boxplot(%s ~ %s

data = df

0
Data
PromptBeginner5 minmarkdownQuality: 24

fit_aov <- aov(%s ~ %s

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

fit <- lm(%s ~ %s

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

t.test(%s ~ %s

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

if (is.null(datafile)) datafile <- paste0(project_name

.csv)

0
Data
PromptBeginner5 minmarkdownQuality: 24

check_data <- function(df

topnlevels = 8) {

0
Data
PromptBeginner5 minmarkdownQuality: 24

saveRDS(df

data_clean.rds)

0
Data
PromptBeginner5 minmarkdownQuality: 24

fitaov <- aov(outcomevar ~ group_var

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

t.test(outcomevar ~ groupvar

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

abline(lm(outcome_var ~ predictor

data = df)

0
Data
PromptBeginner5 minmarkdownQuality: 24

df <- read.csv(your_data.csv

stringsAsFactors = FALSE)

0
Coding & Debugging
PromptBeginner5 minmarkdownQuality: 24

- arrows: code = 1 (head at start)

code = 2 (head at end

0
Data
PromptBeginner5 minmarkdownQuality: 24

- Formula interface: `pairs(~ var1 + var2 + var3

data = df)`.

0
Data
PromptBeginner5 minmarkdownQuality: 24

- Formula interface: `cor.test(~ x + y

data = df) — note the ~` with no LHS.

0