smooth_measurement

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. It explicitly states 'changes the measurement in place', alerting the agent to the mutating nature. However, it does not disclose reversibility, permissions, or potential side effects on other dependent measurements.

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 a single sentence, front-loaded with the action and resource, and the parenthetical adds the crucial in-place caveat economically. Every word earns its place, with no filler or repetition.

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?

For a simple mutation tool with fully documented parameters, the description adequately covers purpose and side effect. The lack of output schema and annotations is partially mitigated by the clear in-place note, though it could mention which measurement types support smoothing or whether the operation is reversible.

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 100%, with both 'measurement' and 'smoothing' already documented. The description adds no extra parameter semantics beyond what the schema provides, such as the UUID vs index distinction or the enum values, so it meets the baseline without adding value.

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 action (apply smoothing) and the resource (a measurement), and notes the in-place effect, distinguishing it from read-only measurement tools. 'Fractional-octave smoothing' further specifies the exact operation, making the purpose unmistakable.

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 implies the tool is used when smoothing is needed, but provides no explicit guidance on when to choose this over alternatives like 'arithmetic' or 'average_measurements'. No exclusions or prerequisites are stated, leaving the agent to infer usage from the operation name alone.

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