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Run npx skillmds@latest add nandanosql/pol-probe in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Pol Probe free to use?

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Who published Pol Probe?

nandanosql (@nandanosql) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Pol Probe by nandanosql — Agent Skill

Name: Pol Probe
Author: nandanosql

File contents

Purpose

Evaluate product-market fit using Sean Ellis' approach — measuring the "very disappointed" threshold and emotional attachment to quantify PMF strength and identify what makes your product a must-have.

Application

PMF Survey Template

# Product-Market Fit Survey

## Core Questions

### Q1: The Sean Ellis Test
"How would you feel if you could no longer use [Product Name]?"
- Very disappointed
- Somewhat disappointed
- Not disappointed
- I no longer use [Product Name]

### Q2: Must-Have Drill-Down
"What is the primary benefit you receive from [Product Name]?"
[Open text]

### Q3: Who Benefits Most
"What type of person do you think would benefit most from [Product Name]?"
[Open text]

### Q4: Improvement
"How can we improve [Product Name] for you?"
[Open text]

### Q5: Alternative
"What would you use as an alternative if [Product Name] were no longer available?"
[Open text]

Analysis Template

# PMF Assessment: [Product Name]

**Survey Date:** [Date]
**Responses:** [N]

## Sean Ellis Score
| Response | Count | % |
|----------|-------|---|
| Very disappointed | [#] | [%] ← **THIS IS YOUR PMF SCORE** |
| Somewhat disappointed | [#] | [%] |
| Not disappointed | [#] | [%] |

**Benchmark:** ≥40% "Very disappointed" = strong PMF

## PMF Health: [🟢 Strong (>40%) | 🟡 Getting there (25-40%) | 🔴 Not yet (<25%)]

## Key Insights

### Who loves us most?
[Segment analysis of "Very disappointed" respondents]

### Core value (from Q2)
[Top themes from must-have benefit answers]

### Must-have persona (from Q3)
[Who do they say benefits most? This is your ICP.]

### Alternatives (from Q5)
[What they'd switch to — this is your competition]

## Recommendations
1. **Double down on:** [What the "very disappointed" segment values most]
2. **ICP focus:** [Target the segment with highest PMF score]
3. **Improve:** [Themes from improvement feedback]

Quality Rubric

Dimension	0	1	2
Sample	<20 responses	20-50 responses	>50 from active users
Segmentation	Overall score only	By plan/tier	By behavior segment
Analysis	Score only	Score + themes	Score + segments + actions

References

Related Skills

skills/growth/retention-deep-dive/SKILL.md — PMF drives retention
skills/growth/pol-probe-advisor/SKILL.md — Interactive assessment
skills/discovery/survey-design/SKILL.md — Survey methodology

External Frameworks

Sean Ellis, Hacking Growth (2017)
Rahul Vohra (Superhuman), PMF Engine

Skill type: Component Domain: Growth & Optimization

---name: pol-probedescription: Evaluate product-market fit using Sean Ellis' "Product of Love" approach — measuring user disappointment, must-have percentage, and emotional attachment to identify PMF strength.---## PurposeEvaluate product-market fit using Sean Ellis' approach — measuring the **"very disappointed" threshold** and emotional attachment to quantify PMF strength and identify what makes your product a must-have.---## Application### PMF Survey Template```markdown# Product-Market Fit Survey## Core Questions### Q1: The Sean Ellis Test"How would you feel if you could no longer use [Product Name]?"- Very disappointed- Somewhat disappointed- Not disappointed- I no longer use [Product Name]### Q2: Must-Have Drill-Down"What is the primary benefit you receive from [Product Name]?"[Open text]### Q3: Who Benefits Most"What type of person do you think would benefit most from [Product Name]?"[Open text]### Q4: Improvement"How can we improve [Product Name] for you?"[Open text]### Q5: Alternative"What would you use as an alternative if [Product Name] were no longer available?"[Open text]```### Analysis Template```markdown# PMF Assessment: [Product Name]**Survey Date:** [Date]**Responses:** [N]## Sean Ellis Score| Response | Count | % ||----------|-------|---|| Very disappointed | [#] | [%] ← **THIS IS YOUR PMF SCORE** || Somewhat disappointed | [#] | [%] || Not disappointed | [#] | [%] |**Benchmark:** ≥40% "Very disappointed" = strong PMF## PMF Health: [🟢 Strong (>40%) | 🟡 Getting there (25-40%) | 🔴 Not yet (<25%)]## Key Insights### Who loves us most?[Segment analysis of "Very disappointed" respondents]### Core value (from Q2)[Top themes from must-have benefit answers]### Must-have persona (from Q3)[Who do they say benefits most? This is your ICP.]### Alternatives (from Q5)[What they'd switch to — this is your competition]## Recommendations1. **Double down on:** [What the "very disappointed" segment values most]2. **ICP focus:** [Target the segment with highest PMF score]3. **Improve:** [Themes from improvement feedback]```---## Quality Rubric| Dimension | 0 | 1 | 2 ||-----------|---|---|---|| **Sample** | <20 responses | 20-50 responses | >50 from active users || **Segmentation** | Overall score only | By plan/tier | By behavior segment || **Analysis** | Score only | Score + themes | Score + segments + actions |---## References### Related Skills- `skills/growth/retention-deep-dive/SKILL.md` — PMF drives retention- `skills/growth/pol-probe-advisor/SKILL.md` — Interactive assessment- `skills/discovery/survey-design/SKILL.md` — Survey methodology### External Frameworks- Sean Ellis, *Hacking Growth* (2017)- Rahul Vohra (Superhuman), PMF Engine---**Skill type:** Component**Domain:** Growth & Optimization

Frequently asked questions

Pol Probe