How do I install the Cypress Transformer Xray skill?

Run npx skillmds@latest add jovd83/cypress-transformer-xray in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Cypress Transformer Xray safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Cypress Transformer Xray?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Cypress Transformer Xray free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Cypress Transformer Xray?

jovd83 (@jovd83) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Cypress Transformer Xray by jovd83 — Agent Skill

Name: Cypress Transformer Xray
Author: jovd83

Cypress Transformer Xray

Legacy Cypress-specific alias for Xray case export. Prefer the standalone `test-artifact-export-skill` skill for transforming approved test cases into Xray-ready artifacts, and use this only when Cypress-local conventions must be preserved explicitly.

jovd83 Updated Sep 17, 2026

File contents

Telemetry & Logging

[!IMPORTANT] All usage of this skill must be logged via the Skill Dispatcher to ensure audit logs and wallboard analytics are accurate: ./log-dispatch.cmd --skill <skill_name> --intent <intent> --model <model_name> --reason <reason> (or ./log-dispatch.sh on Linux)

Transforming Test Cases to Xray

Use this skill to convert narrative test cases into Xray import artifacts.

Action

Inputs:

source scenarios in TDD, BDD, or plain-text form,
the target Xray structure if the project already uses one,
any required Jira or Xray metadata conventions.

Output contract:

an Xray-compatible JSON or CSV payload,
a field-mapping table when the user wants the transformation planned before generation,
or a normalized scenario table ready for downstream import tooling.

Mapping rules:

preserve scenario titles, steps, expected outcomes, and requirement references,
keep Jira or issue identifiers intact where possible,
preserve ordered steps and execution meaning,
call out any source fields that have no clean Xray destination.

Frequently asked questions