What it does
Amazing PsyCoder removes coding barriers from psychology research by automating experiment design, code generation, and statistical analysis. It guides researchers through structured workflows—from initial hypothesis to publishable results—without requiring programming expertise.
How it works
The skill uses seven integrated components: a task orchestrator plus six specialized sub-skills covering experiment programming and data analysis. For experiments, it guides you through design confirmation → code generation → code auditing. For data analysis, it routes you through analysis design → script generation → reproducibility checking.
Supports PsychoPy (Python), jsPsych (JavaScript), and Psychtoolbox (MATLAB) for experiment creation. For analysis, generates R (tidyverse/lme4) or Python (pandas/statsmodels) reproducible scripts. Covers 38 classic paradigms (Stroop, N-back, IAT, etc.) and 60+ statistical methods.
Use cases
- Experiment design: Convert research ideas into working task code in hours instead of weeks
- Data analysis: Match your scientific question to optimal statistics with transparent decision logic
- Lab reproducibility: Generate auditable code that runs identically across environments
- Methodology transparency: Create design registries and analysis plans reviewers can verify
Who benefits
Psychology students and researchers building experimental tasks, behavioral scientists needing systematic analysis workflows, labs seeking reproducible research infrastructure, and anyone currently struggling with RT accuracy, randomization, or statistical method selection.