Skills ux-researcher-designer
📦

ux-researcher-designer

Content revision r2 Safe ⚙️ External commands

Turn UX Research into Actionable Personas

Research data can be difficult to synthesize into clear design direction. This skill generates structured personas, scenarios, confidence labels, and design implications from user records.

Supports: Claude Codex Code(CC)
📊 76 Adequate

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "ux-researcher-designer" from https://skillstore.io/skills/davila7-ux-researcher-designer.md and its manifest at https://skillstore.io/api/skills/davila7-ux-researcher-designer/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/davila7-ux-researcher-designer.md Signed manifest GET /api/skills/davila7-ux-researcher-designer/manifest Signed lockfile GET /api/skills/davila7-ux-researcher-designer/lockfile

Test it

Using "ux-researcher-designer". Twenty-eight workplace users, mostly weekly desktop users, report sharing and reporting needs.

Expected outcome:

  • Archetype: Business User
  • Primary goal: Professional productivity
  • Scenario: Team collaboration with sharing and feedback tracking
  • Confidence: Medium, based on 28 records
  • Design implication: Support professional workflows and enterprise controls

Using "ux-researcher-designer". Twelve mobile users report daily use, quick interactions, and difficulty accessing desktop-only features.

Expected outcome:

  • Archetype: Mobile First
  • Value: Flexibility
  • Scenario: Complete a quick task while commuting
  • Confidence: Low, based on 12 records
  • Design implication: Prioritize responsive, touch-optimized interactions

Using "ux-researcher-designer". Sixty daily desktop users each use more than ten distinct features and prioritize workflow speed.

Expected outcome:

  • Archetype: Power User
  • Primary goal: Complete tasks efficiently
  • Interaction focus: Advanced feature efficiency
  • Confidence: High, based on 60 records
  • Design implication: Provide shortcuts and power features

Security Audit

Safe
v9 • 7/23/2026 Open versioned report

The only static finding is a false positive because Markdown backticks format a documented Python command and do not invoke Ruby or a shell. The local script has no subprocess, network, credential, or filesystem behavior, and no semantic threats or prompt injection were found.

2
Files scanned
540
Lines analyzed
0
Review items
0
False positives ignored

Risk Factors

⚙️ External commands (1)
SKILL.md:22
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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Open versioned report
Security Assessment

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Academic citations (APA · BibTeX · CFF)

APA citation

davila7. (2026). ux-researcher-designer security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-ux-researcher-designer/audits/9

BibTeX citation

@techreport{davila7-davila7-ux-researcher-designer-2026, author = {davila7}, title = {ux-researcher-designer security audit report (audit version 9)}, institution = {Skillstore}, year = {2026}, number = {9}, url = {https://skillstore.io/skills/davila7-ux-researcher-designer/audits/9}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "ux-researcher-designer security audit report (audit version 9)" version: "unspecified" type: report authors: - name: "davila7" date-released: "2026-07-23" url: "https://skillstore.io/skills/davila7-ux-researcher-designer/audits/9" identifiers: - type: other value: "skillstore:davila7-ux-researcher-designer:audit:9" description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score
davila7 Recommended Current

davila7-ux-researcher-designer

Skillstore Score 76
Evidence Confidence High
Skillstore usage 9
Updated

2026-08-21

alirezarezvani

alirezarezvani-ux-researcher-designer

Skillstore Score 75
Evidence Confidence High
Skillstore usage 15
Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High
45
Architecture
85
Maintainability
87
Content
70
Community
91
Spec Compliance

What You Can Build

Synthesize Discovery Research

Synthesize prepared behavioral records and interview notes into an evidence-linked draft persona for a discovery study.

Guide Interface Concepts

Translate a defined user segment into needs, frustrations, scenarios, and interface implications before concept design.

Compare Product Segments

Create comparable persona drafts for separately prepared segments when planning priorities with a cross-functional team.

Try These Prompts

Create a Basic Persona 
Use the persona generator with these prepared user records. Return the archetype, demographics, goals, frustrations, scenario, and confidence label: [records]
Add Interview Evidence 
Generate a persona from these user records and interview insights. Separate observed inputs, heuristic conclusions, default content, and design implications: [data]
Compare Prepared Segments 
Generate one persona for each prepared segment. Compare archetypes, behaviors, needs, frustrations, confidence labels, and design implications without merging records: [segments]
Review Segment Sensitivity 
Run a sensitivity review across alternative segment definitions. Identify changed classifications, stable findings, default assumptions, evidence gaps, and recommended validation work: [dataset]

Best Practices

  • Normalize fields and remove direct identifiers before providing research records.
  • Prepare meaningful segments separately because each generator call produces one aggregate persona.
  • Label defaults and heuristic conclusions, then validate them with participants and additional evidence.

Avoid

  • Do not present generated names, default quotes, or template scenarios as direct research evidence.
  • Do not treat one aggregate persona as proof of distinct market segments.
  • Do not describe the sample-size label as statistical confidence or validated research quality.

Frequently Asked Questions

Can the included command read my research file?
No. The command runs built-in sample data and only changes the output format when given the json argument.
Can this skill create multiple personas automatically?
Not from one dataset. Prepare segments separately and run the generator once for each segment.
Does it analyze raw interview transcripts?
No. Interview insights must be prepared as structured goals, needs, motivations, values, and quotes.
How is the confidence label calculated?
It is low through 20 records, medium through 50 records, and high above 50 records.
Does the script send or store research data?
No. It has no network or file-writing behavior, but supplied data and generated output remain visible in the execution environment.
Which AI tools support this skill?
The marketplace metadata lists Claude, Codex, and Claude Code as supported tools.

Developer Details

Author

davila7

License

MIT

Skillstore revision

r2

Version notice

The author did not declare a version.

Repository

https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/creative-design/ux-researcher-designer

Ref

c43861a65bb95efcae259cd161c9d6f4dc7eec6f

Maintenance freshness

7/25/2026

Usage

7 downloads · 211 views

File structure

📁 scripts/

📄 persona_generator.py

📄 SKILL.md