# WebAsk — Open Answer Analysis

> Analyses free-text answers from a WebAsk survey: finds themes, counts frequency and picks representative quotes. Use when someone asks to read the comments, understand what respondents write about, or summarise open answers. Requires the hosted WebAsk MCP server (Streamable HTTP: https://mcp.webask.io/mcp/v1) and the user’s own WebAsk account/API key. Public skill files: MIT, original publisher WebAsk; hosted service plans and limits apply. English source; Russian counterpart: https://github.com/WebAskio/webask-mcp/tree/main/skills/webask-open-answers

- Skill: `dmitry-molchanov/webask-open-answer-analysis` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add dmitry-molchanov/webask-open-answer-analysis`
- Raw SKILL.md: https://api.skillmd.com/api/skills/dmitry-molchanov/webask-open-answer-analysis/raw
- Safety review: pending
- Works with: any agent that reads SKILL.md (Claude Code, Claude.ai, Cursor, Codex, Windsurf, 60+ more)
- Category: Docs & Writing
- Author: Dmitry Molchanov (https://skillmd.com/u/dmitry-molchanov)
- Updated: 2026-10-01
- Page: https://skillmd.com/skills/dmitry-molchanov/webask-open-answer-analysis

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# Analysing free-text answers

Open questions give the most valuable and the least convenient material: a hundred
lines of text that appear in the report as a plain list. The job is to turn them
into a few themes with numbers.

Reply to the person in the language they write in.

## Collect

`get_quiz_report_inputs` — all text answers for one question. If several questions
have text, take them one at a time: mixing answers to different questions produces
mush.

To filter first, use `get_quiz_report`, then pull texts for the selected responses.

## Analyse

1. **Extract themes** by meaning, not by wording: "waited long", "waited forty
   minutes" and "the queue" are one theme.
2. **Count.** How many answers per theme and what share of those who answered.
3. **Separate the empty ones.** "No", "all fine", "-" form a "no content" group:
   do not theme them, but do not hide them either — the size says something.
4. **Pick quotes.** One or two per theme, verbatim, the most characteristic.
5. **Note sentiment** where it is distinguishable: one theme can carry different
   attitudes.

## How to present

Themes by descending frequency. For each: a theme name in your own words, the
count, the share, one quote.

At the end: the two or three themes that recur most, which is what is worth acting
on.

## Honesty rules

- **Do not invent themes.** If the answers do not group, say so.
- **Do not bend results to expectations.** If they expected price complaints and
  people write about deadlines, report deadlines.
- **Quote verbatim**, typos included: a tidied quote stops being evidence.
- **Do not conclude from five answers.** Say the data is thin.

## What not to do

- **Do not mix answers to different questions** in one analysis.
- **Do not surface quotes containing personal data** — strip phone numbers and
  names out of the quote.
- **Do not suggest a plan upgrade or lead to payment.** If a limit is hit, state
  the fact and stop.