set_measure_statistics

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

No annotations are present, so the description carries the full burden. It discloses that reset clears history data and gives a count range, but says nothing about the enable flag, persistence, permissions, or side effects of changing count, leaving key mutation behavior opaque.

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 short and front-loaded: purpose statement followed by parameter notes. It avoids repetition and waste, though the parenthetical '(mean/min/max/... over N acquisitions)' is slightly loose.

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, but for a 3-parameter configuration tool with no annotations, the description omits usage context and the enable parameter's effect. It covers count and reset at a basic level but is incomplete.

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?

Schema description coverage is 0%, and the description documents count (meaning and range) and reset (clears history) but completely omits the enable parameter. It adds useful semantics for two of three parameters, but the gap for enable remains significant.

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 identifies the operation as controlling measurement statistics (mean/min/max over N acquisitions), which is a specific resource and effect. It does not explicitly differentiate from siblings like measure_statistics_item or set_measure_histogram, but the core purpose is clear.

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?

No when-to-use guidance or alternatives are provided. An agent can infer it configures statistics, but there is no condition for choosing this tool over sibling measurement or statistics tools.

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