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netcare-io

jira-xray-cloud-mcp

by netcare-io

Xray Create Test

xray_create_test

Create Xray Test issues in Jira with manual steps, Gherkin scenarios, or unstructured definitions to organize test cases for Xray Cloud.

Instructions

Create an Xray Test issue (manual steps, Gherkin or unstructured definition).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsNoSteps, for step-based (manual) tests.
gherkinNoGherkin scenario, for Cucumber tests.
projectYesJira project key or id.
summaryYes
test_typeNoXray test type name, e.g. 'Manual', 'Cucumber', 'Generic'.Manual
folder_pathNoTest Repository folder, e.g. '/Regression'.
extra_fieldsNoAdditional Jira fields for the new issue, in Jira REST format, e.g. {"description": "...", "labels": ["smoke"], "fixVersions": [{"name": "1.0"}]}.
unstructuredNoFree-text definition, for Generic tests.
preconditionsNoPrecondition keys or ids to link.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the write profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), so the description's main added value is that the created issue is an Xray Test with one of three definition modes. It says nothing about required permissions, duplicate-summary behavior, or what happens on conflicting definition inputs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler or restated boilerplate. It is terse to the point of being a fragment, but nothing is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 9 parameters, two required, and an output schema present, the description does not need to explain return values. However, for a creation tool with three mutually exclusive definition payload styles, the lack of routing between test_type and steps/gherkin/unstructured leaves a real gap for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 89%, so the schema already documents nearly every parameter. The description echoes the definition modes (steps/Gherkin/unstructured) but adds no mapping detail such as 'Manual => steps, Cucumber => gherkin, Generic => unstructured' that would help the agent pick the right field.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Create an Xray Test issue') and enumerates the three definition flavors the tool supports, which distinguishes it from sibling create_* tools for preconditions, test sets and test plans. It does not explicitly name those siblings, but the resource noun is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance and no alternatives named. The agent must infer on its own whether to use this rather than xray_import_tests_bulk or xray_add_test_step, and nothing tells it which definition type to pick for a given input.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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