read_raw_motion

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

With no annotations, the description carries the full behavioral disclosure burden. It does disclose the expected return content (raw 3-axis data for three sensors) and characterizes the data as low-level. However, it omits potential behavioral details such as requiring an active device connection, units, sampling behavior, or error conditions, so it is only moderately transparent.

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 compact and front-loaded: it states the core action first, then the purpose, then the return content. No sentence is wasted, and the Returns section is clearly structured.

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?

For a simple zero-parameter read tool with no output schema, the description adequately explains what the tool returns and why an agent would use it. It falls slightly short of a 5 because it omits specifics like units, exact data shape, or whether the reading is a one-shot sample, but it remains sufficient for correct selection and 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 100% schema coverage, so the baseline is 4. The description adds no parameter-specific information, but none is needed since there are no parameters to document.

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 a specific action and resource: reading raw accelerometer, gyroscope, and magnetometer data. It also distinguishes itself from processed-orientation siblings by emphasizing 'raw' and 'low-level,' so an agent can separate it from read_quaternion, read_euler_angles, and read_orientation.

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 custom processing' gives clear context for when to use this tool versus higher-level sensor interpretation tools. It does not explicitly name alternatives or state when not to use it, but the contrast with processed orientation tools is implied strongly enough.

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