Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add wdavidturner/product-skills --skill pmf-surveygit clone --depth 1 https://github.com/wdavidturner/product-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wdavidturner/product-skills/pmf-survey)<a href="https://agentmods.dev/skills/wdavidturner/product-skills/pmf-survey"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/pmf-survey/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/wdavidturner/product-skills/pmf-survey"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/pmf-survey.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.01176 |
| Opus 5 | $0.00048 | $0.00588 |
| Sonnet 5 | $0.00019 | $0.00235 |
| Haiku 4.5 | $0.00010 | $0.00118 |
Grade A, and why
pmf-survey scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PMF Survey (Product-Market Fit Survey)
What It Is
The PMF Survey is a method to measure and systematically improve product-market fit. The core insight: you can put a number on product-market fit, and you can use that number to write your roadmap.
The key question: "How would you feel if you could no longer use this product?"
- Very disappointed - "I'd be devastated. I need this."
- Somewhat disappointed - "I'd be bummed but I'd find something else."
- Not disappointed - "I wouldn't really care."
Sean Ellis discovered that companies with 40% or more "very disappointed" responses almost always grew successfully, while those under 40% struggled. This benchmark has held across thousands of companies.
Rahul Vohra at Superhuman took this further: he built an engine that uses survey responses to algorithmically generate a roadmap guaranteed to increase PMF score.
When to Use It
Use the PMF Survey when you need to:
- Quantify product-market fit before making major investment decisions
- Decide whether to pivot or double down
- Prioritize your roadmap based on what will actually move the needle
- Identify your best customer segment (who loves you most)
- Track PMF over time as you iterate
- Make the case to investors with data, not gut feeling
When Not to Use It
- You have fewer than 30 active users (sample too small)
- Users haven't had enough time to experience value (survey too early)
- The product is employer-mandated (users had no choice)
- You want to validate a hypothesis without building (use JTBD instead)
Patterns
Detailed examples showing how to apply the PMF Survey correctly. Each pattern shows a common mistake and the correct approach.
Critical (get these wrong and you've wasted your time)
| Pattern | What It Teaches |
|---|---|
| survey-question-wording | Use the exact wording - variations invalidate the benchmark |
| who-to-survey | Only survey users who experienced the core value |
| forty-percent-benchmark | 40% is a threshold, not a target - understand what it means |
| ignoring-somewhat-disappointed | The "somewhat disappointed" segment is your growth engine |
| segment-before-action | You must segment responses before acting on feedback |
What ships with it
19 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- patterns/_template.md 460 B
- patterns/acting-on-not-disappointed.md 1.7 KB
- patterns/doubling-down-vs-fixing.md 1.9 KB
- patterns/enterprise-vs-consumer.md 1.7 KB
- patterns/follow-up-questions.md 1.7 KB
- patterns/forty-percent-benchmark.md 1.6 KB
- patterns/high-expectation-customers.md 1.9 KB
- patterns/ignoring-somewhat-disappointed.md 1.8 KB
- patterns/main-benefit-filter.md 1.8 KB
- patterns/pivot-vs-persevere.md 1.7 KB
- patterns/sample-size-myths.md 1.6 KB
- patterns/segment-before-action.md 2.0 KB
- patterns/survey-question-wording.md 1.5 KB
- patterns/tracking-over-time.md 1.7 KB
- patterns/who-to-survey.md 1.5 KB
- patterns/wrong-timing.md 1.5 KB
- references/pmf-scorecard.md 3.4 KB
- references/pmf-survey-playbook.md 8.3 KB
- references/pmf-survey-template.md 1.2 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 97 lines · 95 tokens per session scan A 32fec478cbf5
pmf-survey is a skill published in the GitHub repository wdavidturner/product-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 95 tokens to every session and 1,176 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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