TEXT⚡ 7K uses📋 GPT-4, Gemini
Data Set Analyzer & Reporter
Generate comprehensive analysis reports.
Analyze [DATA_DESCRIPTION] with columns [COLUMNS] rows [ROWS] for goal [GOAL]. Descriptive stats, distribution, correlation, 5 key insights, 3 suggested visualizations, 3 actionable recommendations.
Variables
DATA_DESCRIPTIONCOLUMNSROWSGOAL
TEXT⚡ 5K uses📋 GPT-4, Claude
Statistical Analysis Advisor
Choose and apply statistical tests.
Advise for [RESEARCH_QUESTION] with data [DATA_TYPE] (N=[N]) variables [VARIABLES] in [LANGUAGE]. Recommended test, assumptions, power analysis, effect size, code snippets, interpretation guide.
Variables
RESEARCH_QUESTIONDATA_TYPENVARIABLESLANGUAGE
CODE⚡ 6K uses📋 GPT-4, Gemini
Data Cleaning & Preprocessing Script
Generate data cleaning scripts.
Cleaning for [DATASET_DESCRIPTION] columns [COLUMNS] with issues [ISSUES] in [LANG]. Missing values, outliers, duplicates, type casting, normalization, validation, logging of changes.
Variables
DATASET_DESCRIPTIONCOLUMNSISSUESLANG
TEXT⚡ 5K uses📋 GPT-4, Claude
A/B Test Analyzer
Analyze A/B tests rigorously.
A/B test: Control [CONTROL] visitors ([CONTROL_CONV] conv, [CONTROL_RATE]%), Variant [VARIANT] visitors ([VARIANT_CONV] conv, [VARIANT_RATE]%). Alpha: [ALPHA]. Lift, CI, p-value, power, MDE, Bayesian analysis, segments, recommendation.
Variables
CONTROLCONTROL_CONVCONTROL_RATEVARIANTVARIANT_CONVVARIANT_RATEALPHA
TEXT⚡ 4K uses📋 GPT-4, Gemini
Dashboard & KPI Designer
Design data-driven dashboards.
Dashboard for [DOMAIN/DEPT] for goal [GOAL] audience [AUDIENCE] using [TOOLS] from [DATA_SOURCES]. 15-20 KPIs, 4-6 panels (chart type + metric + filter), refresh, drill-downs, alerts.
Variables
DOMAIN/DEPTGOALAUDIENCETOOLSDATA_SOURCES
TEXT⚡ 4K uses📋 GPT-4
Data Storytelling Template
Transform findings into narratives.
Data story from [FINDINGS] about [TOPIC] to [AUDIENCE] for goal [GOAL]. Hook (stat/question), context, insight 1-3 (data + viz + implication), conclusion, CTA.
Variables
FINDINGSTOPICAUDIENCEGOAL
TEXT⚡ 4K uses📋 GPT-4, Gemini
Time Series Forecaster
Forecast time series data.
Forecast [METRIC] for [DOMAIN] with historical [PERIOD]. Methods: ARIMA, Prophet, exponential smoothing, moving average. Train/test split, error metrics (MAE, RMSE, MAPE), confidence intervals. Seasonality, trend, cycle decomposition. 3-month forecast.
Variables
METRICDOMAINPERIODFREQUENCY
TEXT⚡ 4K uses📋 GPT-4
Cohort Analysis Builder
Build cohort retention analyses.
Cohort analysis for [METRIC] (retention/revenue/engagement). Cohorts by: acquisition date, signup month, traffic source. Periods: weekly for first 8 weeks, then monthly. Retention curve, cohort heatmap, comparison to benchmark. Actionable insights from drop-off points.
Variables
METRICSOURCECOHORTSPERIODS