adjust_control

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

With no annotations, the description fully carries behavioral disclosure. It details verification process, output structure, lifecycle states, and failure handling with specific error codes, leaving little ambiguity about tool behavior.

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

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

Well-organized into sections (Purpose, Inputs, Output, Verification, Failure), but somewhat verbose. Every sentence is informative, though some redundancy exists (e.g., repeated default values).

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

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

Covers inputs, outputs, verification guidance, failure handling, and edge cases (tolerance defaults for discrete/continuous). Without an output schema, the description provides sufficient structure for understanding return values. Complete for the tool's complexity.

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

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

Schema coverage is 88%, so baseline is 3. The description adds value by explaining default tolerance for discrete vs continuous controls, default maxAttempts, and the requirement of exactly one of selector or element_id, which aids correct parameter usage.

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

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

The description clearly states it adjusts a numeric control value with verification, specifying it's for slider-like controls with numeric values or value ranges. This distinguishes it from sibling tools like tap, swipe, or type_text.

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

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

Provides verification guidance on preferred adjustment methods (direct platform, then increment/decrement, coordinate fallback as degraded) and advises using expect_state for readback. Does not explicitly list when not to use, but context implies it's for numeric controls.

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