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rahulkr
by rahulkr

set_font_scale

Adjust Android device font scaling for accessibility testing. Set values from 0.85 (small) to 1.3 (largest) to verify UI responsiveness across different text sizes.

Instructions

Set system font scale (0.85 = small, 1.0 = normal, 1.15 = large, 1.3 = largest). Useful for testing font scaling accessibility.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNo
device_serialNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'set_font_scale' tool. It is registered via the @mcp.tool() decorator and sets the system font scale using ADB by running the settings command.
    @mcp.tool()
    def set_font_scale(scale: float = 1.0, device_serial: str | None = None) -> str:
        """
        Set system font scale (0.85 = small, 1.0 = normal, 1.15 = large, 1.3 = largest).
        Useful for testing font scaling accessibility.
        """
        return run_adb([
            "shell", "settings", "put", "system", "font_scale", str(scale)
        ], device_serial)
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates this is a system-level setting change ('Set system font scale') and mentions accessibility testing purpose, but doesn't disclose important behavioral aspects like whether changes persist across reboots, require specific permissions, affect all apps or just the current session, or have any side effects on other display properties.

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?

The description is perfectly concise with two focused sentences that each earn their place. The first sentence states the purpose with concrete values, and the second sentence provides the usage context. There's zero wasted language or redundancy.

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?

Given this is a system configuration tool with no annotations, 2 parameters (one well-explained, one undocumented), and an output schema exists (reducing need to describe return values), the description does reasonably well. It covers the core functionality and testing context but leaves gaps about the device_serial parameter and some behavioral implications of changing system settings.

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?

With 0% schema description coverage, the description must compensate for the lack of parameter documentation in the schema. It provides excellent semantic context for the 'scale' parameter by defining the meaning of specific values (0.85=small, 1.0=normal, etc.), which is crucial information not in the schema. However, it doesn't mention the 'device_serial' parameter at all, leaving one of the two parameters completely undocumented.

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?

The description clearly states the tool's purpose with a specific verb ('Set') and resource ('system font scale'), including concrete scale values (0.85-1.3) with accessibility testing context. It distinguishes from sibling tools like 'change_density' or 'reset_screen_size' by focusing specifically on font scaling rather than other display properties.

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?

The description provides clear context for when to use this tool ('Useful for testing font scaling accessibility'), which implicitly suggests it's for accessibility testing scenarios rather than general UI adjustments. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools.

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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