measure_tracks

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds real value beyond that: it discloses the single-render-pass batching behavior and the exact metrics returned, which matters since no output schema exists. It does not mention scope limits or output ordering, keeping it just short of a 5.

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 with zero waste. The capability and its returned metrics are front-loaded, with the sibling-routing guidance second. Every clause earns its place.

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 no output schema, the description carries the return-value burden and does describe the returned table's contents, which is adequate. Parameters are schema-covered and safety is annotated, so the only minor gap is not stating scope defaults or scale/units beyond the LUFS label.

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%, so track selection, start_bar, and end_bar are already fully documented in the schema, including 1-based bar semantics and fractional bars. The description adds nothing further about parameters, so the baseline 3 applies.

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?

States a specific verb (Measures) and resource (many tracks) and enumerates exactly what is returned (max short-term LUFS, peak, brightness, energy band). It explicitly names the sibling it replaces, analyze_audio, so an agent can distinguish the two without opening schemas.

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?

Gives an explicit when-to-use condition ('when balancing a mix') and names the alternative ('instead of analyze_audio track by track'), with the reason ('one call instead of dozens'). Nothing is left to inference.

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