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/foundation-persona

Generates an evidence-calibrated product or marketing persona using the canonical v2.5 output contract. Use when shaping artifact perspective, stress-testing decisions, or framing product and GTM strategy.

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product-on-purpose-pm-skills
72668 skills6 agents11 commands2 hooks
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$ npx -y skills add product-on-purpose/pm-skills --skill foundation-persona --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/foundation-persona

Context preview

The summary Claude sees to decide when to auto-load this skill.

Generates an evidence-calibrated product or marketing persona using the canonical v2.5 output contract. Use when shaping artifact perspective, stress-testing decisions, or framing product and GTM strategy.

SKILL.md

foundation-persona.SKILL.md
name: foundation-persona
description: Generates an evidence-calibrated product or marketing persona using the canonical v2.5 output contract. Use when shaping artifact perspective, stress-testing decisions, or framing product and GTM strategy.
license: Apache-2.0
metadata:
  classification: foundation
  version: "2.6.1"
  updated: 2026-08-16
  category: research
  frameworks: [triple-diamond, lean-startup, design-thinking]
  author: product-on-purpose

<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->

Persona Builder

This skill produces decision-usable personas from one canonical template pack.

Supported Modes

  • `product`
  • `marketing`
  • `buyer` as input alias for `marketing` (output remains labeled `Marketing`)

Generated `agent` mode is out of scope for `v2.5.0`. If the user asks for `agent`, ask them to choose `product` or `marketing`.

When to Use

  • Before drafting PM or GTM artifacts that need a clear persona viewpoint
  • When teams disagree on priorities and need behavior-grounded tradeoff framing
  • When assumptions and confidence levels must be explicit for decision review
  • When tailoring downstream work (PRD, stories, launch, messaging, enablement) to a specific user or buyer profile

When NOT to Use

  • You need the job context rather than the person -> use `define-jtbd-canvas`; the canvas captures what customers hire products to do, the persona captures who they are
  • You are mapping internal stakeholders, not customers -> use `discover-stakeholder-summary`
  • You have raw interviews to synthesize first -> use `discover-interview-synthesis`; a persona built on unsynthesized notes inherits their noise
  • No evidence exists at all and a real decision rides on the persona: gather research first; the skill labels assumptions honestly but cannot substitute for evidence

Instructions

When asked to generate a persona, follow these steps:

1. **Resolve mode and intent** Determine whether the request is `product` or `marketing` (`buyer` alias allowed). If mode is omitted, ask for mode selection. If execution must continue without reply, default to `product` and state that fallback explicitly.

2. **Collect context and evidence** Use user-provided context first (goals, audience, domain, constraints, sources). If evidence is thin, continue generation but mark gaps and calibrate confidence.

3. **Select exactly one template** Use `references/TEMPLATE.md` and choose exactly one of:

  • `Product Persona Template`
  • `Marketing Persona Template`

4. **Generate a complete artifact** Fill the selected template end-to-end:

  • header + one-sentence core-reality statement
  • metadata table
  • `Persona Card`
  • sections `1` through `11`
  • `Evidence & Confidence`

5. **Enforce mode boundaries**

  • Product mode: focus on workflow behavior, decision patterns, friction, quality bar, and product tradeoffs.
  • Marketing mode: focus on buying triggers, evaluation criteria, committee dynamics, objections, messaging, and GTM implications.

6. **Apply evidence and confidence policy**

  • Use `High|Medium|Low` confidence with rationale.
  • Distinguish validated evidence from assumptions.
  • State open questions and governance follow-up.

7. **Finalize for direct use** Remove template guidance blockquotes (`>` notes) from the final output. Ensure narrative entries are concrete and decision-changing, not placeholder bullets.

Output Contract (v2.5.0)

  • Use one mode only (`Product` or `Marketing`) per output.
  • Keep section numbering and headings from the selected template.
  • Preserve the evidence table plus validated/assumed/open-questions/governance blocks.

Quality Checklist

Before finalizing, verify:

  • [ ] Exactly one mode is used and clearly labeled
  • [ ] `buyer` inputs are normalized to `Marketing`
  • [ ] Header, core-reality statement, metadata table, and `Persona Card` are present
  • [ ] All `1` through `11` sections from the selected template are present and complete
  • [ ] Includes/not-valid boundaries are explicit in the metadata and narrative
  • [ ] Evidence table is populated with concrete sources
  • [ ] Confidence is `High`, `Medium`, or `Low` with rationale
  • [ ] `Validated`, `Assumed`, `Open questions`, and `Governance` blocks are present
  • [ ] Template authoring notes (`>` guidance lines) are removed from the completed output

Examples

See `references/EXAMPLE.md` for a completed sample output.

Read more
Ships withproduct-on-purpose-pm-skills

68 plug-and-play, best-practice product management skills for AI agents: 30 Triple Diamond phase + 11 foundation + 12 utility + 15 tool (Foundation Sprint + Design Sprint). Plus 6 sub-agents, workflows, 200+ output samples, guides, and CI-enforced contracts. Apache 2.0.

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