---
name: mohitagw15856/survey-design-basics
source: https://app.decimal.ai/s/mohitagw15856-survey-design-basics@1/SKILL.md
source_sha256: 37f499ae3fac
---

# Survey Design Basics Skill

Surveys fail at design time, invisibly: the leading question ("How much do you love our new feature?"), the double-barrel ("Is the product fast and reliable?" — which one?), the scale with no honest exit (forced positivity), and the twenty-minute questionnaire that only the delighted and the furious complete. By the time results arrive, the damage is unfixable — the data measures the questionnaire, not the population. Design discipline is cheap and front-loaded: neutral wording, one question per question, scales with real options, brutal length editing, a pilot, and the analysis plan written *before* launch — because a question you don't know how you'll analyze is a question you shouldn't ask.

## What This Skill Produces

- **The question set** — each question bias-checked and single-barreled, mapped to the decision it informs
- **The scale choices** — response options with the reasoning (and the don't-know/NA exits that keep answers honest)
- **The length edit** — the cut list, with the completion-rate logic
- **The pilot + analysis plan** — five test-takers before launch, and the how-each-question-gets-analyzed table written first

## Required Inputs

Ask for these if not provided:
- **The decision the survey feeds** — what will be done differently based on results; questions that inform no decision get cut first ([kpi-tracker-design](../kpi-tracker-design/SKILL.md) so-what logic)
- **The audience and reach method** — who gets it, how, and the response-rate reality (the selection caveat gets written into the analysis plan now, not discovered later)
- **The draft questions, if any** — existing drafts get the bias audit; the classic sins are findable and fixable
- **Prior interview themes** — surveys size what interviews surfaced ([interview-synthesis](../interview-synthesis/SKILL.md) hands off here); a survey inventing its own hypotheses mid-questionnaire does both jobs badly

## Framework: The Design Rules

1. **Neutral wording or measured applause:** every question checked for leading language ("how much do you love" → "how would you rate"), loaded framing, and social-desirability pull (people report the virtuous answer — anonymity and neutral framing are the mitigations). The test: could a respondent tell which answer you're hoping for?
2. **One barrel per question:** "fast and reliable" splits into two; "satisfied with price and support" splits into two — every "and" in a question is a fork respondents resolve invisibly, corrupting both halves.
3. **Scales with honest exits:** balanced options (as many negative as positive), a genuine midpoint where neutrality is real, and *don't-know / not-applicable* where respondents might legitimately not know — forced answers are fabricated data with a UI. Consistent scale direction throughout (flipping positive-left to positive-right mid-survey harvests inattention, not insight).
4. **Length is a completion-rate decision:** every question costs respondents; the audit asks each one "which decision do you inform?" and cuts the merely-interesting. Target minutes stated honestly up front; the nice-to-know questions die so the need-to-know ones get answered by more than the furious-and-delighted.
5. **Pilot, then the pre-launch analysis plan:** five real-ish people take it aloud (confusions found here cost nothing; found in results, everything) — and the analysis table (question → how it's cut → what result triggers what) exists *before* launch. It catches unanalyzable questions, pre-commits interpretations (guarding against results-fishing), and makes the results memo a fill-in exercise.

## Output Format

# Survey: [purpose] → [the decision] — target: [N] min

## The Questions
| # | Question (bias-checked) | Scale + exits | Informs which decision |
|---|---|---|---|
[The cut list below: killed questions + why]

## Scale & Flow Notes
[Direction consistency · midpoint/NA reasoning · anonymity level and its social-desirability logic]

## The Pilot
[Five think-aloud runs · the confusion fixes]

## The Analysis Plan (pre-launch)
[Question → the cut/comparison → the result-to-action mapping · the selection caveat, pre-written]

## Quality Checks

- [ ] No question telegraphs its hoped-for answer
- [ ] Zero double-barrels survived
- [ ] Every scale has honest exits and consistent direction
- [ ] Every surviving question maps to a decision; the cut list exists
- [ ] The analysis plan predates the launch

## Anti-Patterns

- [ ] Do not lead — a survey that flatters its author measures the flattery
- [ ] Do not force answers — missing "don't know" manufactures opinions from noise
- [ ] Do not ask everything interesting — length is paid in completion bias
- [ ] Do not launch without the analysis plan — unanalyzable questions are respondent-time theft
- [ ] Do not report percentages without the selection caveat — who answered is half the result