get_meter_value

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so thoroughly. It explains that value is null when the instrument cannot produce a reading, null while enabled is false, the source is reported, and that the counter may return 0 or null for the first three seconds after enabling—an important non-obvious behavior an agent would otherwise misread as a real null reading.

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 front-loaded with the core read operation, then adds only behaviorally relevant details: allowed kind values, unit mapping, null semantics, the configure_meter prerequisite, and the settling-time caveat. Every sentence carries useful information, and the structure is logical from summary to operational caveats.

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?

Even without an output schema or annotations, the description is complete enough for an agent to call the tool correctly: it specifies the parameter values, expected return fields (value, unit, mode, settings, source), null behavior, and timing caveats. No critical operational detail is missing for a single-parameter read tool.

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 schema only says kind is a string with 0% description coverage, so the description must compensate. It explicitly defines the allowed values ('counter' or 'dvm'), links them to the returned unit and mode, and explains the effect of the parameter—making the single parameter fully meaningful.

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 opens with a specific verb and resource: 'Read the current frequency counter or digital voltmeter value with its unit.' It further clarifies that kind selects the meter mode and distinguishes this read operation from other instrument tools, so an agent can identify what this tool does and what it applies to.

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 description gives clear usage context: use kind='counter' or 'dvm', configure_meter must be called first to turn the meter on, and the counter needs about three seconds to settle after being enabled. It does not explicitly compare this tool to siblings or state when not to use it, so it misses the exclusion/alternative guidance that would make it a 5.

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