get_predicted_response

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

With no annotations provided, the description carries the full burden. It discloses that this is a prediction computed from current EQ filters, which is a key behavioral trait. However, it doesn't state whether the operation is read-only, what happens if no EQ filters exist, or any other side effects or limitations.

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, well-structured sentence that conveys the essential information without any wasted words. It is front-loaded with the core purpose and adds the crucial 'not a re-measurement' distinction at the end.

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 read-only tool with one well-documented parameter and no output schema, the description provides the essential context: what it returns and its predictive nature. It doesn't explain return format, but that was not required. Overall, complete for the tool's complexity.

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 input schema covers the single 'measurement' parameter thoroughly (UUID vs index, stability). Since schema description coverage is 100%, the description need not add parameter details, and it doesn't — baseline of 3 is appropriate.

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 tool returns a summary of the predicted frequency response after applying current EQ filters, and explicitly notes it's REW's prediction, not a re-measurement. This distinguishes it from siblings like get_frequency_response, though it lacks a direct imperative verb like 'get' or 'retrieve'.

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 phrase 'not a re-measurement' implies using this when a prediction is desired instead of actual measurement, but no explicit alternatives or exclusions are named. The context is helpful but doesn't fully guide selection among sibling tools.

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