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List Devices

list_devices

Retrieve a list of controllable devices from local ADB or Mobilerun Cloud, filtered by state, type, name, or country. Use returned IDs as device arguments for other tools.

Instructions

Devices you can control. scope: local (adb devices) | cloud (Mobilerun Cloud, needs MOBILERUN_CLOUD_API_KEY) | all. Cloud filters: state (creating, assigned, ready, terminated, ...), type, name, country, page, pageSize (or a filters dict). Any listed id works as the device argument of every tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
pageNo
typeNo
scopeNolocal
stateNo
countryNo
filtersNo
pageSizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, this description carries the full burden and does well: it discloses the auth prerequisite for cloud scope and, importantly, that any listed device id is valid as the device argument of every other tool — a non-obvious behavioral contract. It stops short of describing pagination behavior or result volume.

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?

Front-loaded with the resource, then scope semantics, then filters, then the cross-tool id note. It is dense and largely waste-free, though the pipe-delimited fragments read slightly telegraphically.

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 an 8-param tool with no annotations, the description covers scope, auth, filters, and the downstream use of returned ids; an output schema exists so return values need not be spelled out. Only pagination semantics and default behavior with no arguments are unaddressed.

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 0%, so the description must compensate, and it largely does: it names scope values, the cloud filter fields (state, type, name, country, page, pageSize, filters dict), and enumerates several state values. Only the precise behavior of the filters dict and defaults are left implicit.

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 identifies the resource ('Devices you can control') and, paired with the name list_devices, the operation is unambiguous. It does not need to differentiate from siblings since no other tool enumerates devices, but the fragmentary phrasing never states the verb outright, keeping it short of a 5.

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?

Explicitly tells the agent how to choose between the local, cloud, and all scopes, and flags that cloud requires MOBILERUN_CLOUD_API_KEY. It offers no exclusions or negative guidance (e.g. when not to call it), so it lands at a clear-context 4.

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