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 mfwarren/entrepreneur-claude-skills --skill product-market-fitgit clone --depth 1 https://github.com/mfwarren/entrepreneur-claude-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/mfwarren/entrepreneur-claude-skills/product-market-fit)<a href="https://agentmods.dev/skills/mfwarren/entrepreneur-claude-skills/product-market-fit"><img src="https://agentmods.dev/badge/skills/mfwarren/entrepreneur-claude-skills/product-market-fit/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/mfwarren/entrepreneur-claude-skills/product-market-fit"><img src="https://agentmods.dev/badge/skills/mfwarren/entrepreneur-claude-skills/product-market-fit.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 | $0.00003 | $0.00645 |
| Opus 5 | $0.00002 | $0.00322 |
| Sonnet 5 | $0.00001 | $0.00129 |
| Haiku 4.5 | $0.00000 | $0.00064 |
Grade A, and why
product-market-fit 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.
Product-Market Fit
PMF surveys, Sean Ellis test, retention analysis, and pivot frameworks.
Purpose
Determine whether you've found product-market fit and, if not, what to change. PMF is the single most important milestone for any startup.
Workflow
Step 1: Gather Context
- Product/service description
- Current customer count and engagement
- How customers find you today
- Retention/repeat usage data (if available)
- What customers say they love (and hate)
Step 2: Sean Ellis Test Design
Survey question: "How would you feel if you could no longer use [product]?"
- Very disappointed
- Somewhat disappointed
- Not disappointed
- N/A — I no longer use it
Benchmark: 40%+ "Very disappointed" = PMF signal
Design the full survey (5-8 questions) to understand:
- Who are the most passionate users?
- What's the primary benefit they get?
- What would they use as an alternative?
- How did they discover you?
Step 3: PMF Assessment
Based on data provided:
- Strong PMF signals: High retention, word-of-mouth growth, pull from customers
- Weak PMF signals: High churn, feature requests that change the core, price sensitivity
- No PMF signals: Growth only from paid acquisition, low engagement, high support volume
Step 4: Pivot Framework (if needed)
If PMF isn't there, evaluate:
- Zoom in: Double down on the feature users love most
- Zoom out: Your feature should be a platform
- Customer pivot: Same product, different audience
- Need pivot: Same audience, different problem
- Channel pivot: Same product, different distribution
Step 5: Action Plan
Concrete next steps based on assessment.
Output Format
## PMF Assessment: [Product]
### Current Signals
| Signal | Status | Evidence |
|--------|--------|----------|
| Retention | [Strong/Weak] | [Data] |
| Word of mouth | [Strong/Weak] | [Data] |
### Sean Ellis Survey
[Survey questions]
### Assessment
[PMF status and reasoning]
### Recommended Actions
1. [Action]
2. [Action]
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 · 3 tokens per session scan A bcdcfcc394a1
product-market-fit is a skill published in the GitHub repository mfwarren/entrepreneur-claude-skills (67 stars, last pushed 7mo ago), licensed MIT. It adds 3 tokens to every session and 645 once invoked, about $0.0000 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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