get_light

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

readOnlyHint=true already covers the safety profile, so the bar is lower, and the description still adds real context: the call also enumerates model capabilities (colour temperature range, supported effects). That dual-purpose behavior is not derivable from the annotations or the empty schema.

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?

Two short sentences, front-loaded with the primary function and followed by the secondary capability-listing behavior. No filler, no restatement of the tool name.

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 an output schema present, return values need not be explained, and the description still summarizes them plus the capability discovery feature. For a zero-parameter read tool this is essentially complete; only explicit guidance on when to reach for it over nothing is missing.

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?

Zero parameters, so the baseline is 4; there is nothing for the description to disambiguate. The description correctly spends no words on argument semantics.

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?

States a specific verb and resource ("Read the light's power, mode, brightness, colour, effect and battery") and enumerates exactly what comes back, which cleanly separates it from the set_* siblings. It stops short of naming an alternative explicitly, but the read-vs-set distinction is unambiguous.

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 read verb implies the natural use case (inspect current state before or after calling setters), but there is no explicit when-to-use or when-not-to-use statement. An agent can infer the workflow, yet nothing routes it explicitly.

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