Foundation persona
Skill product-on-purpose/pm-skills/skills/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.From its SKILL.md
npx -y skills add product-on-purpose/pm-skills --skill foundation-personaAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its file declares
Copied from the file, not written here
The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
4.4 KB, 880 tokens by cl100k_base, as published. Nobody here has run it
Persona Builder
This skill produces decision-usable personas from one canonical template pack.
Supported Modes
productmarketingbuyeras input alias formarketing(output remains labeledMarketing)
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:
-
Resolve mode and intent Determine whether the request is
productormarketing(buyeralias allowed). If mode is omitted, ask for mode selection. If execution must continue without reply, default toproductand state that fallback explicitly. -
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.
-
Select exactly one template Use
references/TEMPLATE.mdand choose exactly one of:Product Persona TemplateMarketing Persona Template
-
Generate a complete artifact Fill the selected template end-to-end:
- header + one-sentence core-reality statement
- metadata table
Persona Card- sections
1through11 Evidence & Confidence
-
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.
-
Apply evidence and confidence policy
- Use
High|Medium|Lowconfidence with rationale. - Distinguish validated evidence from assumptions.
- State open questions and governance follow-up.
- Use
-
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 (
ProductorMarketing) 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
-
buyerinputs are normalized toMarketing - Header, core-reality statement, metadata table, and
Persona Cardare present - All
1through11sections 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, orLowwith rationale -
Validated,Assumed,Open questions, andGovernanceblocks are present - Template authoring notes (
>guidance lines) are removed from the completed output
Examples
See references/EXAMPLE.md for a completed sample output.
What ships with it: 4 files
35.7 KB alongside SKILL.md
evals/
- trigger-fixtures.json4.0 KB
references/
- EXAMPLE.md9.2 KB
- TEMPLATE.md21.8 KB
- HISTORY.md617 B
Gives 0 of the 12 instructions most product growth skills give in 880 tokens
Counted across 694 of the 879 authors here whose files we hold, read 2026-09-06
- Check for product marketing context firstin 49 of 694, across 20 files
- Validate the why before building featuresin 18 of 694, across 4 files
- Respond to every comment in real-timein 17 of 694, across 6 files
- Structure launch marketing across three channel typesin 16 of 694, across 4 files
- Recruit early users one-on-onein 13 of 694, across 2 files
- Ask one question at a timein 13 of 694
- Rank features using ICE scoringin 12 of 694, across 3 files
- Identify primary conversion goalin 11 of 694, across 3 files
- Identify traffic contextin 11 of 694, across 3 files
- Evaluate headline effectivenessin 11 of 694, across 3 files
- Check visual hierarchy and scannabilityin 11 of 694, across 3 files
- Run product diagnosticsin 11 of 694, across 3 files
Said here and by no other author read
- Resolve mode and intent
- Collect context and evidence
- Select exactly one template
- Generate a complete artifact
- Enforce mode boundaries
- Apply evidence and confidence policy
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.