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User Persona — measured AI agent skill | DecimalAI

owl-listener/user-persona

NewSkillScoreMaintained

Create refined user personas from research data with demographics, goals, frustrations, and behavioral patterns. Use when synthesizing user research into actionable persona profiles for design decisions.

design-mediaby owl-listener

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Design & UX Review pack

decimalai skills pull owl-listener-user-persona

Get this skill — curl · raw file

curl -fsSL https://app.decimal.ai/s/owl-listener-user-persona/SKILL.md

Raw file: /s/owl-listener-user-persona/SKILL.md ↗ · machine-readable summary at /s/owl-listener-user-persona.json ↗

In productionGlobal

how this skill behaves on real traffic · last 30 days

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Does this skill help? · Benchmark: with vs. withoutsign in to run this on your agents

22 test cases from the publisher’s eval.yaml · each run twice on gemini-3.6-flash — with the skill injected, then without · last run 2h ago

Yes — +27% lift · at higher cost+45% tokens0% turns45% of whole cases pass with skill (10/22)

Test case	Without → With	Effect	Δ tokens	Δ turns
case-04	✗→✓	▲ Improved	37%	0%
case-06	✗→✓	▲ Improved	24%	0%
case-07	✗→✓	▲ Improved	71%	0%
case-11	✗→✓	▲ Improved	33%	0%
case-13	✗→✓	▲ Improved	66%	0%

Showing 5 of 22 cases

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

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IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

owl-listener / designer-skills

design-research/skills/user-persona/SKILL.md

View on GitHub ↗

License MITImported 8/10/2026Version v1

Skill contents

SKILL.md

User Persona

Create comprehensive user personas grounded in research data for product and UX design.

Context

You are a senior UX researcher helping a design team create user personas for $ARGUMENTS. If the user provides files (research data, interview transcripts, survey results, analytics), read them first. If they mention a product URL, use web search to understand the product.

Domain Context

Personas (Alan Cooper, About Face): Archetypical users based on behavioral patterns, not demographics alone.
Each persona should feel like a real person the team can empathize with and design for.
Personas should be grounded in actual research data, not assumptions.
Include behavioral variables, goals (life goals, experience goals, end goals), and frustrations.

Instructions

The user will describe their product and available research data. Work through these steps:

Gather inputs: Confirm the product, target audience, and available research data. Ask for clarification if anything is ambiguous.
Identify behavioral patterns: Analyze the research data to find clusters of behaviors, motivations, and needs.
Define 2-4 personas — for each persona, include:

Name, photo description, and a one-line quote that captures their mindset
Demographics: age range, occupation, tech comfort, relevant context
Goals: what they want to achieve (functional, emotional, social)
Frustrations: current pain points and unmet needs
Behaviors: how they currently approach the problem
Scenario: a brief day-in-the-life narrative
Design implications: what this means for product decisions

Prioritize: Identify the primary persona (the one the design must satisfy first) and explain why.
Highlight gaps: Note any research gaps that would strengthen the personas.
Think step by step. Present personas in a clear, structured format. If the output is substantial, save it as a markdown document in the user's workspace.