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ado_testplans_create

Creates a new test plan in Azure DevOps, automatically generating a root suite; returns the rootSuiteId for use when adding child suites via ado_testsuites_create. Requires vso.test_write scope.

Instructions

Create a new test plan in Azure DevOps. ADO automatically creates a root suite alongside the plan — the response includes rootSuiteId. Pass rootSuiteId as parentSuiteId when calling ado_testsuites_create to add child suites. Requires vso.test_write PAT scope.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesTest plan name
endDateNoPlan end date in ISO 8601 format, e.g. '2024-01-14'.
projectYesProject to create the test plan in
areaPathNoArea path, e.g. 'MyProject\\MyTeam'. Defaults to project root.
iterationNoIteration path, e.g. 'MyProject\\Sprint 1'.
startDateNoPlan start date in ISO 8601 format, e.g. '2024-01-01'.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description discloses a non-obvious side effect (ADO auto-creates a root suite), the response containing rootSuiteId, and the required vso.test_write PAT scope. These add real behavioral value beyond the structured metadata.

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

Conciseness5/5

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

Three sentences, each earning its place: purpose, non-obvious side effect plus next step, and auth requirement. The most critical operation is front-loaded, and no filler or redundancy exists.

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

Completeness4/5

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

For a creation tool with no output schema, the description covers the main purpose, side effects, the important returned field, and the required scope. It could be slightly more complete by stating what the response contains besides rootSuiteId, but given the low complexity and the presence of sibling guidance, it is adequately complete.

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

Parameters4/5

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

Schema coverage is 100%, so the schema fully documents all parameters. The description adds a connection between the return value (rootSuiteId) and a further tool call, which gives the rootSuiteId context beyond the schema. However, it does not add detail about individual parameters themselves, so a baseline of 4 with this small extra is fair.

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

Purpose5/5

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

States a specific verb and resource: 'Create a new test plan in Azure DevOps.' It also distinguishes itself from sibling reads like ado_testplans_list/get and related create-like tools by describing the automatic root suite creation, which is a unique behavior.

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

Usage Guidelines4/5

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

Gives clear usage context by describing the follow-up workflow: 'Pass rootSuiteId as parentSuiteId when calling ado_testsuites_create to add child suites.' It also mentions the required PAT scope. It lacks an explicit 'when not to use' but the siblings are sufficiently different and the context makes the intended use obvious.

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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