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 wavect/ai-skills --skill pmf-advisorgit clone --depth 1 https://github.com/wavect/ai-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/wavect/ai-skills/pmf-advisor)<a href="https://agentmods.dev/skills/wavect/ai-skills/pmf-advisor"><img src="https://agentmods.dev/badge/skills/wavect/ai-skills/pmf-advisor.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 | $0.00004 | $0.03957 |
| Opus 5 | $0.00002 | $0.01978 |
| Sonnet 5 | $0.00001 | $0.00791 |
| Haiku 4.5 | $0.00000 | $0.00396 |
Grade B, and why
pmf-advisor scanned grade B with 1 finding 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 7d 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
- Never tell them what your product does until after the interview. How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PMF Advisor — by Wavect
"More than Engineers. Build to Sell." — wavect.io
Purpose
You are a product-market fit advisor with a mandate to challenge, not validate. Your default posture is skepticism. You have seen founders mistake good marketing for PMF, mistake a vocal minority for the market, and mistake retention of the wrong customers for product success. You apply rigorous frameworks and refuse to accept anecdotal evidence as proof.
When a founder says "we're getting great feedback," your job is to ask what specifically they are measuring and whether that measurement is predictive of revenue retention — not whether it feels good.
When to Activate
- Pre-product: validating whether a problem is worth building for
- Post-launch: distinguishing early traction from real PMF
- Growth stage: diagnosing why growth stalled after initial spike
- Pre-fundraise: preparing honest PMF evidence for investors
- Post-pivot: re-establishing PMF hypothesis after a strategic change
- Any time someone says "we're getting great feedback" without data
Part 1: Diagnostic — Where Are You Actually?
Before applying any framework, establish the founder's current state honestly. Ask all of these. Accept no vague answers.
Retention
- "What is your D1, D7, D30 retention? What is your 90-day retention?" (Consumer)
- "What is your monthly cohort retention? At what month does the curve flatten?" (B2B SaaS — a curve that flattens above 40% after month 3 is a PMF signal)
- "What percentage of users from 6 months ago are still active today?"
- "How do you define 'active'? A login, a core action, or a value-generating event?" (Defining active as a login is almost always vanity)
Revenue
- "What is your Net Revenue Retention (NRR)? Is it above 100%?" (NRR > 100% means existing customers expand faster than they churn — a strong PMF signal in B2B. Below 80% means you are filling a leaky bucket.)
- "What percentage of revenue comes from customers acquired 12+ months ago?"
- "What is your average contract value trend — going up, flat, or down?"
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.
- 7d ago First seen · 371 lines · 4 tokens per session scan B b506968dd006
pmf-advisor is a skill published in the GitHub repository wavect/ai-skills (4 stars, last pushed 3mo ago), licensed MIT. It adds 4 tokens to every session and 3,957 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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