user-interview

To extract actionable insights from user interview transcripts, process plain text files to identify pain points, feature requests, and jobs-to-be-done. The skill cross-references existing research and PRDs to label themes as VALIDATED, CHALLENGED, or NEW, outputting a shareable Markdown research synthesis.

The best way to synthesize qualitative research from multiple interviews is processing one to three transcripts to generate per-interview insight cards. It extracts sentiment, jobs-to-be-done, and a representative quote bank, saving an executive summary report for team sharing.

Yes, you can cross-reference new interview themes against existing PRDs and research. The skill validates findings by labeling extracted pain points and feature requests as VALIDATED, CHALLENGED, or NEW based on the provided context.

User research synthesis works specifically for analyzing a small batch of one to three interviews. It is designed for quick post-interview debriefs, extracting per-interview themes and opportunity scoring to inform your next roadmap decision.

You create a quote bank and executive summary from plain text transcripts by running the skill on your interview files. It automatically extracts representative quotes, pain points, and sentiment, saving a concise Markdown report to your outputs folder.

Jobs-to-be-done analysis in user research transcripts identifies the core tasks users are trying to accomplish. This skill extracts these jobs alongside pain points and feature requests from plain text interviews to inform product decisions.