Best use case
Survey Design is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Design and analyze surveys for product validation and user research
Teams using Survey Design should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/survey-design/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Survey Design Compares
| Feature / Agent | Survey Design | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Design and analyze surveys for product validation and user research
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Survey Design Skill
## Overview
Specialized skill for designing and analyzing surveys for product validation. Enables product teams to gather structured feedback through well-designed surveys and interpret results with statistical rigor.
## Capabilities
### Survey Design
- Design PMF surveys (Sean Ellis test)
- Create NPS survey implementations
- Build feature validation surveys
- Generate survey question banks
- Design onboarding feedback surveys
- Create churn exit surveys
### Question Engineering
- Write unbiased survey questions
- Design appropriate response scales
- Create skip logic and branching
- Optimize question order
- Balance survey length vs completion
### Analysis
- Analyze survey response data
- Calculate statistical confidence in results
- Segment analysis by user attributes
- Identify response patterns and themes
- Generate actionable insights from data
## Target Processes
This skill integrates with the following processes:
- `product-market-fit.js` - PMF survey design and analysis
- `beta-program.js` - Beta participant surveys
- `customer-advisory-board.js` - CAB feedback collection
- `jtbd-analysis.js` - Jobs-based survey questions
## Input Schema
```json
{
"type": "object",
"properties": {
"surveyType": {
"type": "string",
"enum": ["pmf", "nps", "csat", "feature-validation", "exit", "onboarding", "custom"],
"description": "Type of survey to design"
},
"objective": {
"type": "string",
"description": "Primary objective of the survey"
},
"targetAudience": {
"type": "string",
"description": "Target survey respondents"
},
"hypotheses": {
"type": "array",
"items": { "type": "string" },
"description": "Hypotheses to validate through survey"
},
"maxQuestions": {
"type": "number",
"default": 10,
"description": "Maximum number of questions"
},
"responseData": {
"type": "array",
"description": "Survey response data for analysis (if analyzing existing survey)"
}
},
"required": ["surveyType", "objective"]
}
```
## Output Schema
```json
{
"type": "object",
"properties": {
"survey": {
"type": "object",
"properties": {
"title": { "type": "string" },
"introduction": { "type": "string" },
"questions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"id": { "type": "string" },
"type": { "type": "string" },
"text": { "type": "string" },
"options": { "type": "array", "items": { "type": "string" } },
"required": { "type": "boolean" },
"logic": { "type": "object" }
}
}
},
"estimatedTime": { "type": "string" }
}
},
"analysisFramework": {
"type": "object",
"properties": {
"keyMetrics": { "type": "array", "items": { "type": "string" } },
"segmentationCriteria": { "type": "array", "items": { "type": "string" } },
"successThresholds": { "type": "object" }
}
},
"analysis": {
"type": "object",
"description": "Analysis results if response data was provided",
"properties": {
"responseRate": { "type": "number" },
"keyFindings": { "type": "array", "items": { "type": "string" } },
"segmentInsights": { "type": "object" },
"statisticalConfidence": { "type": "object" },
"recommendations": { "type": "array", "items": { "type": "string" } }
}
}
}
}
```
## Usage Example
```javascript
const survey = await executeSkill('survey-design', {
surveyType: 'pmf',
objective: 'Measure product-market fit for new analytics feature',
targetAudience: 'Active users who have used analytics at least 3 times',
hypotheses: [
'Users find the analytics feature valuable for their workflow',
'Users would be disappointed if the feature was removed'
],
maxQuestions: 8
});
```
## Dependencies
- Survey platform integrations
- Statistical analysis librariesRelated Skills
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