measure_series

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

Discloses key behavioral trait: interval_s behavior differs between mock (instant) and real hardware (waits). No contradictions with missing annotations.

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?

Three sentences covering purpose, implementation detail, and test behavior; could be more concise but no extraneous content.

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?

No output schema; does not specify return format of the time series, data types, or error handling. Incomplete for a measurement 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?

Input schema has 0% description coverage for required params 'args' and 'kwargs'; description mentions only interval_s without mapping it to a parameter.

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?

Clearly states the tool polls one measurement repeatedly and returns a short time series, distinguishing it from single-acquisition siblings like acq_single and measure_snapshot.

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?

Provides implicit usage context (polling repeatedly with interval_s) but lacks explicit when-to-use or when-not-to-use guidance relative to sibling tools.

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