measure_rotation

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only indicates a measurement operation and does not describe permissions, side effects, input source, rate limits, or return format, leaving most behavioral traits undocumented.

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?

The description is a single short sentence with no filler, making it appropriately concise. However, its terse fragment style lacks structure for usage or return-value context, keeping it just below a fully polished definition.

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?

With no annotations, no output schema, and no parameters, the description is the only source of context for the agent. It does not explain what input image is measured, how the measurement is obtained, or what the result looks like, so it is materially incomplete for correct invocation.

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?

The tool has zero parameters and an empty input schema, so there are no parameter semantics to explain. The baseline for a zero-parameter tool is 4, and the description has no parameter-related obligations to meet.

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 states a metric ('how far an image is turned') and a use case ('for a rotation challenge'), but it is a noun phrase rather than a clear verb+resource statement and largely restates the tool name. It does not clarify what the tool returns, how the image is identified, or how it differs from sibling measurement tools like measure_frames or measure_gap.

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?

The phrase 'for a rotation challenge' implies a specific usage context, but there is no explicit guidance on when to use this tool versus alternatives, nor any when-not conditions. An agent can infer the general scenario but must still guess the exact trigger.

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