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 saski/arnesto --skill pmf-surveygit clone --depth 1 https://github.com/saski/arnestoWrote 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/saski/arnesto/pmf-survey)<a href="https://agentmods.dev/skills/saski/arnesto/pmf-survey"><img src="https://agentmods.dev/badge/skills/saski/arnesto/pmf-survey.svg" alt="Measured on agentmods" 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 | $0.00626 |
| Opus 5 | $0.00048 | $0.00313 |
| Sonnet 5 | $0.00019 | $0.00125 |
| Haiku 4.5 | $0.00010 | $0.00063 |
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 4d 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.
This is a copy
100% identical to pmf-survey — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Context
This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work.
Input Requirements
- Context about your product, feature, or problem
- Relevant data, research, or constraints (recommended but optional)
- Clear articulation of what you're trying to achieve
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)
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.
- 4d ago First seen · 65 lines · 95 tokens per session scan A 6364c3245ba8
pmf-survey is a skill published in the GitHub repository saski/arnesto (5 stars, last pushed yesterday), licensed Unlicense. It adds 95 tokens to every session and 626 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to pmf-survey, differing in 0 lines, and is treated as a copy.
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