Data
PromptBeginner5 minmarkdown
- Provide a detailed report with strategies on how to excel in exams
including study tips and areas to focus on.
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Find agent skills by outcome
14,178 skills indexed with the new KISS metadata standard.
Showing 24 of 14,178Categories: Openclaw, Data, Coding & Debugging, Research & Learning, Cursor-rules
Research & Learning
PromptBeginner5 minmarkdown
- Analyze submitted exam papers and identify the type of questions (e.g.
multiple-choice
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Coding & Debugging
PromptBeginner5 minmarkdown
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:
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Data
PromptBeginner5 minmarkdown
- Utilize historical data
patterns
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Data
PromptBeginner5 minmarkdown
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.
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Data
PromptBeginner5 minmarkdown
Small Functional Analyst mode
Functional Analyst Mode
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Data
PromptBeginner5 minmarkdown
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...
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Data
PromptBeginner5 minmarkdown
Probably the most useful standalone thing here. Source it and run `check_data(df)` on any data frame to get a formatted report of dimensions
NA counts
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Data
PromptBeginner5 minmarkdown
│ ├── visualization.md # par
layout
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Data
PromptBeginner5 minmarkdown
│ ├── statistics.md # Hypothesis tests
distributions
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Data
PromptBeginner5 minmarkdown
│ ├── data-wrangling.md # Subsetting traps
apply family
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Coding & Debugging
PromptBeginner5 minmarkdown
I'm a political science PhD candidate who uses R regularly but would never call myself *an R person*. I needed a Claude Code skill for base R — something without tidyverse
without ggplot2
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Data
PromptBeginner5 minmarkdown
# boxplot(%s ~ %s
data = df
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Data
PromptBeginner5 minmarkdown
fit <- lm(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdown
# fit_aov <- aov(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdown
# t.test(%s ~ %s
data = df)
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Data
PromptBeginner5 minmarkdown
if (is.null(data_file)) data_file <- paste0(project_name
.csv)
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Data
PromptBeginner5 minmarkdown
check_data <- function(df
top_n_levels = 8) {
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Data
PromptBeginner5 minmarkdown
# saveRDS(df
data_clean.rds)
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Data
PromptBeginner5 minmarkdown
# fit_aov <- aov(outcome_var ~ group_var
data = df)
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Data
PromptBeginner5 minmarkdown
t.test(outcome_var ~ group_var
data = df)
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Data
PromptBeginner5 minmarkdown
abline(lm(outcome_var ~ predictor
data = df)
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Data
PromptBeginner5 minmarkdown
df <- read.csv(your_data.csv
stringsAsFactors = FALSE)
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Coding & Debugging
PromptBeginner5 minmarkdown
- `arrows`: `code = 1` (head at start)
`code = 2` (head at end
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