verbatim-themeslisted

# Verbatim Theme Analysis Goal: **Systematically code** the open-ended answers of the question/column named in the user's request — build themes, count their frequency, back them with quotes. This is about qualitative depth over the **full** dataset. Result to `reports/`. ## Tool ``` python3 scripts/survey.py <cmd> [...] [--file CSV] ``` Run these from the project root. If `scripts/survey.py` is not there, check `.claude/scripts/survey.py` or locate `survey.py` in the project. - `profile` — column overview; identifies FREETEXT columns (always first). - `text COL [--filter "COL=VALUE"]` — print **all** answers of the column (no `--sample`, so nothing is missed). `--json` for clean downstream handling. - `text COL --filter ...` — free text of a subgroup (e.g. daily users only). `COL` = index (from `profile`) or an unambiguous name part. ## Survey context If a context document sits next to the CSV (`<name>.context.md`, or `survey-context.md` when the folder holds exactly one CSV), read it before coding. The **glossary** is the practical gain here: respondents write in internal shorthand, feature names and abbreviations, and without the glossary you will either misread them or split one theme across several. The **fieldwork circumstances** explain spikes — a release or an outage during the field period shows up as a theme and should be labeled as such, not read as a standing complaint. Code **bottom-up regardless**: themes come from the answers, never from the context d