What problem does it solve?
Survey data is easy to misread: small samples, leading questions, and biased recruitment produce confident-looking numbers that do not hold up. This Skill turns raw survey responses into an honest analysis that states what the data shows, what it does not show, and which conclusions the methodology cannot support.
Core Features & Use Cases
- Methodology audit and per-question analysis: Reviews sample size, recruitment method, and question-design risks, then reports response distributions with qualitative confidence labels tied to sample size.
- Thematic clustering and hypothesis validation: Clusters open-text responses into themes with representative quotes, and marks each hypothesis as SUPPORTED, CONTRADICTED, INCONCLUSIVE, or NOT TESTED BY THIS SURVEY.
- Refusal protocols: Declines to overstate statistical significance from weak samples, biased instruments, or causal claims from cross-sectional data.
- Use Case: You ran an in-product survey with 240 responses testing interest in a new feature. The Skill flags the leading question, segments results by plan tier, surfaces an accuracy-trust concern hidden in open-text answers, and recommends a prototype test instead of a full build.
Quick Start
Analyze these survey responses and tell me what the data shows, what it does not show, and which hypotheses it actually validates.
