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List devices

list_devices
Read-only

The phones and tablets app tests can run on, and their OS versions (latest first). Pass device and osVersion to create_test, update_test, run_test or run_project. A new app test runs on a phone with the latest OS unless you choose otherwise; the version is saved with the test, so it keeps its OS until you change it.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_devices"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), so the bar is lower, yet the description still adds real behavior: results are ordered latest-first, an unspecified new test defaults to the newest OS on a phone, and the OS is pinned at creation until changed. That default-and-persistence semantics is exactly the kind of context annotations cannot convey. It omits list size or freshness/caching details, so not a 5.

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?

Three front-loaded sentences with no filler: what it returns, how to use it, then default behavior. The opening fragment is slightly awkward and the final clause about the saved OS runs long, but every sentence carries information an agent needs.

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?

With no parameters and no output schema, the description must describe the return shape, and it does (phones and tablets with OS versions, newest first), plus the default-selection rule that matters for test creation. Only minor gaps remain, such as whether the list is paginated or filtered by project/platform.

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?

Zero input parameters, which sets the baseline at 4. The description goes a step further by naming the fields the returned objects expose (device, osVersion) and explaining how to feed them into sibling tools, adding meaning the empty schema cannot.

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?

The description names the resource concretely ('the phones and tablets app tests can run on') and the payload fields ('their OS versions'), plus an ordering ('latest first'). It is clearly distinguishable from list_builds, list_projects, and the other list_* siblings, though it opens with a noun fragment rather than an explicit verb, which slightly softens the action statement.

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?

It gives concrete downstream routing: pass device and osVersion to create_test, update_test, run_test, or run_project. That tells the agent exactly why and where this tool's output is consumed. It stops short of stating when not to call it or whether the list is complete for all plan tiers, so it is strong context without full exclusion guidance.

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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