What is xray-testing?

A bridge between a coding agent and Xray, a test-management system that runs inside Jira. It handles test cases, test steps, test plans, executions, and recorded results.

Create and edit Xray tests and preconditions, group tests into sets or plans, run executions, record results, import JUnit or other test reports, and link tests to requirements or bugs.

It removes the need to manually move testing data between Jira, Xray, and test-report files. It also keeps Xray-specific work separate from ordinary Jira issue editing.

xray-testing — Skill for Claude Code by arozumenko

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add arozumenko/sdlc-skills --skill xray-testing

Clone the repo

git clone --depth 1 https://github.com/arozumenko/sdlc-skills

Made for: Claude Code.

Or install sdlc-skills, the plugin that ships this one along with the rest of its 53 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/xray-testing/github.svg)](https://agentmods.dev/skills/arozumenko/sdlc-skills/xray-testing)

Your own site

<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/xray-testing"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/xray-testing/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/arozumenko/sdlc-skills/xray-testing"><img src="https://agentmods.dev/badge/skills/arozumenko/sdlc-skills/xray-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 5,135 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00077	$0.05135
Opus 5	$0.00039	$0.02567
Sonnet 5	$0.00015	$0.01027
Haiku 4.5	$0.00008	$0.00513

Measured 9d ago against content hash b6ddb529678b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

xray-testing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/xray.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/xray-testing/SKILL.md · 435 lines

How it starts

The opening of the file, as written. The whole thing — 435 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Xray — the TMS that lives inside Jira

Xray stores test cases and execution records as Jira issues of specific issue types (Test, Precondition, Test Set, Test Plan, Test Execution). That design is why this skill is separate from atlassian-content: the Jira issue layer (ADF, comments, mentions) is covered there; everything Xray-specific (test steps, preconditions, test run statuses, results import, coverage links) lives here and talks to Xray's own API.

This skill is transport-agnostic (GraphQL / REST / MCP / connector) and deployment-agnostic (Cloud or Server / DC).

When to load this skill

Load when the task involves reading, authoring, linking, or recording results against Xray entities:

Fetching a Test's steps (structured, not the Jira description)
Creating a Test / Precondition / Test Set / Test Plan
Adding or editing steps on a Test
Adding Tests to a Test Set / Test Plan
Creating a Test Execution and reporting Test Run results
Importing results from JUnit / Cucumber / NUnit / TestNG / generic Xray JSON
Linking a Test to a story / requirement / bug for coverage
Querying coverage ("which tests cover PROJ-42?" / "which requirements have no tests?")

Do NOT load for: pure Jira field reads / comment authoring on Xray issue keys — those don't need Xray-specific endpoints. Use atlassian-content for that.

Transport priority — check in this order on every call

MCP is first. The CLI is a fallback. Raw REST / GraphQL is a last resort. Never default to scripts/xray.py when an MCP tool already covers the operation — secrets stay out of agent context when you go through MCP, and an MCP-wired project has already invested in permissions / audit / reliability the CLI can't match.

MCP tools — mcp__<server>__<toolset>_* (e.g. mcp__Elitea_Dev__JiraIntegration_get_issue_details, mcp__dmtools-cli__xray_get_test, mcp__mcp-xray__*). Discover with the host's MCP-listing command (copilot --list-mcp, claude mcp list, Cursor / Windsurf settings panel) and match the tool to the operation. Use the MCP if a matching tool exists, even if the skill's examples show CLI commands.
Bundled CLI — scripts/xray.py (stdlib Python, zero deps). Only when no MCP tool covers the operation, or when the MCP server is offline. The CLI auto-detects Cloud vs Server, caches JWTs, and bakes in the re-fetch + validate discipline (exit 3 on mismatch). See scripts/README.md for the surface.
Raw REST / GraphQL — assemble your own HTTP call. Reserve for debugging or when both MCP and the CLI are unavailable.

Read the full file on GitHub · 435 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

9d ago First seen · 435 lines · 77 tokens per session scan A b6ddb529678b

Subscribe to this mod's changes

xray-testing is a skill published in the GitHub repository arozumenko/sdlc-skills (20 stars, last pushed 4d ago), licensed MIT. It adds 77 tokens to every session and 5,135 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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