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 the UX Researcher Designer…
What this skill helps you do
Use the UX Researcher Designer playbook when you need to improve product discovery, merchandising, and onsite conversion. It gives the operator a repeatable set of checkpoints.
Use the UX Researcher Designer playbook when you need to improve product discovery, merchandising, and onsite conversion. It gives the operator a repeatable set of checkpoints.
Before you start
- Choose one bounded, reversible conversion experiment or merchandising change to test.
- Prepare traffic and funnel data, the current page or theme, product rules, and a measurable hypothesis, removing sensitive fields the trial does not need.
- Record the current conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics, then name the approver and stop conditions.
- Map the data path from source to destination, then review read, write, and administrator scopes separately.
How to test it safely
- Test one normal case, one edge case, and one case with a deliberately missing critical field.
- Compare the result with the pre-test baseline for conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics; do not record time saved alone.
- Review errors, human edits, permissions used, and unresolved exceptions before expanding scope.
- Simulate a timeout, a duplicate event, and a partial destination failure to verify alerts and recovery.
Operator-ready setup plan
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.
Checkpoint: The input boundary, owner, and one primary measure from conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics are written down.
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.
Checkpoint: Every input has a known source, sensitive fields are minimized, and the approver knows what the trial can read or change.
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.
Checkpoint: You have a conversion experiment or merchandising change that a responsible operator can inspect, and it stayed inside the approved boundary.
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.
Checkpoint: conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics has a pre-test baseline, and errors and exceptions are logged separately.
Add monitoring, approval, and recovery
Alert on failures, timeouts, duplicate runs, and permission changes. Keep human approval, idempotency checks, an action log, and a recovery path you have rehearsed.
Checkpoint: A failed run can be traced in logs, bad writes can be reversed, and ownership of recovery is explicit.
Limits to account for
- We checked the public source and resource identity on 2026-07-19. That review does not cover every workflow result, and vendor performance claims are not treated as EcomAgentTools tests.
- A change that lifts one funnel metric can still hurt margin, accessibility, speed, or customer trust.
- This page reflects the review completed on 2026-07-19, not a permanent guarantee. Recheck the current documentation, pricing, and contract terms before production use.
Questions at this experience level
Which permissions should UX Researcher Designer receive?
Grant the smallest scope required for this workflow. Separate read, draft, production-write, and administrator access, and require human approval for high-risk writes.
How should failures be rolled back?
Keep source records, request IDs, versions, before-values, and action logs. Rehearse timeouts, duplicate runs, partial success, and third-party API failure outside production.
What should be monitored after launch?
Monitor success, exceptions, latency, execution cost, unauthorized writes, and conversion rate, revenue per visitor, add-to-cart rate, and guardrail metrics. A completed run is not proof of a safe result.
Creator, original source, and platform proof
Alireza Rezvani
HealthTech CTO and open-source maintainer focused on applied AI, agentic coding, and practical skills for product, research, growth, and operations teams.