measure_series

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

With no annotations provided, the description carries full burden. It discloses the behavior of interval_s in test vs real hardware, indicating the tool respects the settle hook, making mock instant. This adds behavioral context beyond the 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 sentences plus an embedded code block, all concisely front-loaded. First sentence states purpose, second gives use case, third explains key parameter behavior with a test vs hardware distinction. No wasted words.

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?

Given 4 parameters, 2 required, and an output schema (context signal), the description covers the key aspects: polling nature, sampling behavior, and parameter rationale. It might lack prerequisites (e.g., prior configuration), but sibling tools imply those steps exist.

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 coverage is 100%, baseline 3. The description adds value by clarifying that interval_s is honored via the instrument's settle hook, and that 0 polls as fast as possible. It also uses context to explain the behavior, which is not fully captured in the schema descriptions.

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 verb 'poll' and resource 'measurement repeatedly, returning a short time series'. It distinguishes from siblings like measure_snapshot by emphasizing repeated readings over time.

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 explicitly states it's 'useful for watching a value drift or settle' with a concrete example. It also explains when interval_s matters (honored via settle hook) but doesn't explicitly list when not to use it or alternatives.

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