acquisition-channel-ad…
Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.
Select the right Proof of Life (PoL) probe based on hypothesis, risk, and resources. Use this to match the validation method to the real learning goal, not tooling comfort.
$ npx -y skills add deanpeters/Product-Manager-Skills --skill pol-probe-advisor --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/pol-probe-advisorContext preview
The summary Claude sees to decide when to auto-load this skill.
Select the right Proof of Life (PoL) probe based on hypothesis, risk, and resources. Use this to match the validation method to the real learning goal, not tooling comfort.
name: pol-probe-advisor argument-hint: "[hypothesis or risk]" description: Select the right Proof of Life (PoL) probe based on hypothesis, risk, and resources. Use this to match the validation method to the real learning goal, not tooling comfort. intent: >- Guide product managers through selecting the right **Proof of Life (PoL) probe** type (of 5 flavors) based on their hypothesis, risk, and available resources. Use this when you need to eliminate a specific risk or test a narrow hypothesis, but aren't sure which validation method to use. This interactive skill ensures you match the cheapest prototype to the harshest truth—not the prototype you're most comfortable building. type: interactive best_for: - "Choosing the cheapest useful validation method for a risky idea" - "Matching a hypothesis to the right Proof of Life probe" - "Avoiding overbuilding before learning the harsh truth" scenarios: - "Which Proof of Life probe should I use to test demand for this idea?" - "Help me pick the right validation method for an onboarding hypothesis" - "I have a risky AI concept. What PoL probe should I run first?" theme: validation-experiments estimated_time: "15-20 min"
Guide product managers through selecting the right **Proof of Life (PoL) probe** type (of 5 flavors) based on their hypothesis, risk, and available resources. Use this when you need to eliminate a specific risk or test a narrow hypothesis, but aren't sure which validation method to use. This interactive skill ensures you match the cheapest prototype to the harshest truth—not the prototype you're most comfortable building.
This is **not** a tool for deciding *if* you should validate (you should). It's a decision framework for choosing *how* to validate most effectively.
**Works best with:** The hypothesis you want to validate or the risk you want to eliminate. **Also useful:** Your resources (time, budget, engineering access), audience access, and what failure would cost.
Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended `ARGUMENTS:` line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.
**Arriving empty-handed? That works too.** The advisor opens by asking what you're trying to learn, then matches you to one of the 5 probe flavors.
**Example invocation:** `Which probe fits? Hypothesis: mid-market HR teams will trust AI-drafted job descriptions enough to publish them; 2 weeks, no eng support.`
**Common failure mode:** PMs choose validation methods based on tooling comfort ("I know Figma, so I'll design a prototype") rather than learning goal. Result: validate the wrong thing, miss the actual risk.
**Solution:** Work backwards from the hypothesis. Ask: "What specific risk am I eliminating? What's the cheapest path to harsh truth?"
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| Type | Core Question | Best For | Timeline | |------|---------------|----------|----------| | **Feasibility Check** | "Can we build this?" | Technical unknowns, API dependencies, data integrity | 1-2 days | | **Task-Focused Test** | "Can users complete this job without friction?" | Critical UI moments, field labels, decision points | 2-5 days | | **Narrative Prototype** | "Does this workflow earn stakeholder buy-in?" | Storytelling, explaining complex flows, alignment | 1-3 days | | **Synthetic Data Simulation** | "Can we model this without production risk?" | Edge cases, unknown-unknowns, statistical modeling | 2-4 days | | **Vibe-Coded PoL Probe** | "Will this solution survive real user contact?" | Workflow/UX validation with real interactions | 2-3 days |
**Golden Rule:** *"Use the cheapest prototype that tells the harshest truth."*
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✅ **Use this when:**
❌ **Don't use this when:**
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Use [`workshop-facilitation`](../workshop-facilitation/SKILL.md) as the default interaction protocol for this skill.
It defines:
This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
This interactive skill uses **adaptive questioning** to recommend the right PoL probe type based on your context.
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**Agent asks:**
Let's figure out which PoL probe type is right for your validation needs. First, I need some context:
**1. What hypothesis are you testing?** (Describe in one sentence, or use "If [we do X] for [persona], then [outcome]" format)
**2. What specific risk are you trying to eliminate?** Examples:
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