queue_profile

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

No annotations exist, so the description carries the full burden. It does disclose meaningful behavior: the quota (1 read), the HTTP verb (GET), and that computation is local — together implying a read-only, side-effect-free, idempotent operation. It does not, however, address edge cases like an empty queue or no active playback session, nor error behavior.

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 filler. The core purpose and computed fields are front-loaded in the first sentence, and the second adds cost/endpoint context compactly. The emoji is informative (green = cheap quota), not decorative. Every element 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?

For a simple single-optional-parameter tool with no output schema, the description covers purpose, computed fields, quota cost, and the underlying endpoint. The only notable gap is undocumented edge-case behavior (e.g., empty queue, missing active session), but this is minor for a read-only analysis tool that already discloses its compute model.

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%. The single parameter response_format is fully documented in the schema itself ('concise' = human prose, 'detailed' = more fields, 'json' = raw API object). The tool description adds no additional parameter meaning beyond what the schema already provides, so the baseline of 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?

The description states a specific verb and resource: computing a 'composition profile of the current queue', then enumerates the exact computed outputs (unique artists, albums, track-vs-episode mix, longest consecutive block by one artist). This clearly distinguishes it from queue siblings like get_queue (raw item list), get_queue_snapshot (point-in-time capture), and split_queue_plan (planning/mutation prep).

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 scope is implied well enough — an agent can infer this is the tool for composition statistics rather than raw queue access. However, it never explicitly names alternatives or exclusion conditions, such as 'for raw queue items use get_queue' or 'for runtime estimation use queue_runtime_report', despite a large family of queue-related siblings. Guidance is present but left to inference.

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