Find agent skills by outcome

Xcode MCP tools are accessed via mcporter CLI

which bridges MCP servers to standard command-line tools. This skill defines when to use Xcode MCP and when to prefer standard tools.

xcode-mcp (for pi agent)

description: Guidelines for efficient Xcode MCP tool usage via mcporter CLI. This skill should be us...

test

- Provide a detailed report with strategies on how to excel in exams

including study tips and areas to focus on.

code generation for online assessments

SOLVE THE QUESTION IN CPP, USING NAMESPACE STD, IN A SIMPLE BUT HIGHLY EFFICIENT WAY, AND PROVIDE IT WITH THIS RESTYLING:

- Utilize historical data

patterns

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.

Small Functional Analyst mode

Functional Analyst Mode

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...

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

NA counts

│ ├── visualization.md # par

layout

│ ├── statistics.md # Hypothesis tests

distributions

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

apply family

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

without ggplot2

boxplot(%s ~ %s

data = df

fit <- lm(%s ~ %s

data = df)

fit_aov <- aov(%s ~ %s

data = df)

t.test(%s ~ %s

data = df)

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

.csv)

check_data <- function(df

topnlevels = 8) {

saveRDS(df

data_clean.rds)

fitaov <- aov(outcomevar ~ group_var

data = df)

t.test(outcomevar ~ groupvar

data = df)

abline(lm(outcome_var ~ predictor

data = df)