interview-review

Analyzing interview transcripts to generate qualitative insights involves reading export artifacts like 01_transcript.md and 02_causal_chains.md to produce a structured 06_insights.md report. This process consolidates Markdown reports and YAML metadata to surface actionable recommendations.

Qualitative interview analysis using MEC or JTBD methodologies evaluates transcript quality, focus fidelity, and strategy alignment. It processes standard export artifacts to generate structured insights, translating dense interview artifacts into actionable qualitative evaluations.

Yes, you can use markdown reports and YAML metadata to score interview quality by reading 04_scoring_summary.md and 00_meta.yaml. This approach relies on provided Markdown reports and YAML metadata to surface structured evaluation without requiring CSV or JSON parsing.

No, interview review does not require CSV or JSON parsing for transcript exports. It relies entirely on provided Markdown reports and YAML metadata to analyze transcripts, scoring, and causal chains to produce actionable qualitative insights.

The best way to turn interview exports into actionable recommendations is analyzing standard artifacts like 01_transcript.md and 04_scoring_summary.md to generate a 06_insights.md file. This consolidates transcript quality, chain quality, and graph health into a structured evaluation.