read_light_intensity

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

With no annotations, the description carries the full behavioral burden. It makes the non-mutating read behavior clear and reports the return quantity and unit. It does not mention error handling or sensor unavailability, but these are minor gaps for a zero-parameter read.

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 brief and front-loaded, with a single purpose statement and a clear return-value line. Every sentence contributes essential information, and there is no wasted wording.

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?

The description fully identifies what is read, the sensor source, and the return value with units. It is essentially complete for a trivial zero-parameter read, though a note about failure behavior could make it marginally more robust.

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?

There are no parameters, so the schema provides full coverage by definition. The description adds no parameter semantics, but none are needed. The baseline of 4 for zero-parameter tools is appropriate.

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 the specific verb 'Read', the resource being read ('light intensity from the ambient light sensor'), and the unit ('lux'). This distinguishes it from sibling sensor-reading tools like read_temperature or read_humidity.

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 usage context is implied: use this tool when ambient light intensity in lux is needed. However, it does not explicitly mention when not to use it or suggest alternatives such as read_all_sensors for a broader sensor read.

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