Produces the requested working draft
The source is designed to produce the specific draft or structured output described in its instruction, using the information supplied in the conversation.
AdvancedClaude Skills
UX Researcher Designer
UX Researcher Designer is an ecommerce AI skill for Claude Skills, built for teams working with Codex, Claude Code, OpenClaw. Use it to improve a product page,…
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What this Skill does
You are preparing to improve a product page, shopping journey, or checkout experience. Validate one concrete path first: Generate user personas from survey and interview data; Map end-to-end customer journeys for a B2B SaaS onboarding flow. Once it holds up, focus on validating… Start with a small test around “Generate user personas from survey and interview data”, then check whether “Map end-to-end customer journeys for a B2B SaaS onboarding flow” fits the way your team actually works.
What makes it different
Structures the analysis before making a recommendation
The source asks for analysis, classification, ranking, or scoring before it reaches a conclusion or next action.
No installation needed
Copy and paste into a model chat
- Expand and copy the complete original Skill.md below.
- Open a new conversation in a compatible AI model, then paste it into the chat box.
- Add verified task details, run one low-risk example, and review the result before using it in store operations.
Original Skill.md
The complete source is shown below. Copy it from the top right to use it.
You are a Senior UX Designer/Researcher. For personas: prepare user data as JSON (demographics, usage patterns, tech proficiency, pain points), generate archetypes with goals, frustrations (include frequency counts), and design implications; validate with 3-5 real users. Journey maps: define scope, map stages with actions/touchpoints/emotions/pain points/opportunities, score by frequency × severity × solvability. Usability tests: transform vague goals into testable questions, select method (moderated/unmoderated/guerrilla), design task scenarios with scenario/goal/success format, define metrics (completion >80%). Research synthesis: code with GOAL/PAIN/BEHAVIOR/CONTEXT/QUOTE tags, cluster 3+ data points, extract findings with evidence and business impact.Get started
Starter prompts for the main use cases—copy and use them directly.
01Start with one real task
Do not begin with a store-wide rollout. Pick one reversible task where UX Researcher Designer can help you improve product discovery, merchandising, and onsite conversion. Use this when the input boundary, owner, and one primary measure from conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics are written down.
Show prompt and variablesHide prompt and variables
Start with one real task
Do not begin with a store-wide rollout. Pick one reversible task where UX Researcher Designer can help you improve product discovery, merchandising, and onsite conversion. Use this when the input boundary, owner, and one primary measure from conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics are written down.
Use the Skill above to help me with this task: Start with one real task.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not begin with a store-wide rollout. Pick one reversible task where UX Researcher Designer can help you improve product discovery, merchandising, and onsite conversion.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
02Prepare the input and guardrails
Collect only the traffic and funnel data, the current page or theme, product rules, and a measurable hypothesis needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Show prompt and variablesHide prompt and variables
Prepare the input and guardrails
Collect only the traffic and funnel data, the current page or theme, product rules, and a measurable hypothesis needed for this test. Remove unrelated personal data and state which actions must never run automatically. Use this when every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
Use the Skill above to help me with this task: Prepare the input and guardrails.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Collect only the traffic and funnel data, the current page or theme, product rules, and a measurable hypothesis needed for this test. Remove unrelated personal data and state which actions must never run automatically.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
03Inspect the source Skill, then run it
Read the source, installation method, and permission notes before adding UX Researcher Designer to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a conversion experiment or merchandising change that a responsible operator can inspect, and it stayed inside the approved boundary.
Show prompt and variablesHide prompt and variables
Inspect the source Skill, then run it
Read the source, installation method, and permission notes before adding UX Researcher Designer to a separate test project. Keep commands and Skill text exactly as published. Use this when you have a conversion experiment or merchandising change that a responsible operator can inspect, and it stayed inside the approved boundary.
Use the Skill above to help me with this task: Inspect the source Skill, then run it.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Read the source, installation method, and permission notes before adding UX Researcher Designer to a separate test project. Keep commands and Skill text exactly as published.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
04Review it against a baseline
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics has a pre-test baseline, and errors and exceptions are logged separately.
Show prompt and variablesHide prompt and variables
Review it against a baseline
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time. Use this when conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics has a pre-test baseline, and errors and exceptions are logged separately.
Use the Skill above to help me with this task: Review it against a baseline.
Task details: [TASK_DETAILS]
Constraints or policies to follow: [CONSTRAINTS]
Do not judge the result by fluency. Compare it with source data, the current SOP, and the pre-test baseline; record factual errors, omissions, and editing time.
Return a practical result and clearly flag anything that needs human review.Replace these variables
[TASK_DETAILS]- The facts, context, or source material for this task.
[CONSTRAINTS]- Replace this placeholder with your verified store-specific information.
Risks and operating notes
Use the minimum customer data needed
The workflow may need an order reference or case facts. Do not paste payment details, full addresses, or unrelated order history into a model conversation; redact them unless they are essential to the decision.
Alireza Rezvani
HealthTech CTO and open-source maintainer focused on applied AI, agentic coding, and practical skills for product, research, growth, and operations teams.
Risk, permissions, and limitations
Review third-party permission scopes before providing store data. Never paste payment credentials, customer passwords, or unnecessary personal data into a model. Outputs must be checked by the operator responsible for the workflow.
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