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

The description discloses the asynchronous queue-then-poll behavior, which is not evident from the annotations alone. It also adds an ownership requirement, giving the agent a basis to check permissions before invoking. No contradiction with annotations; readOnlyHint=false aligns with 'Queue' being a write operation.

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, zero filler. The primary action and prerequisite are front-loaded, and the follow-up polling instruction is placed directly after. Every word 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 an async job-queueing tool with an output schema, the description is complete: it states the action, target, ownership requirement, and how to retrieve the result. The sibling tool list and output schema provide additional context, and nothing essential is missing.

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 schema already documents all three parameters with complete descriptions (100% coverage), so the description need not add more. It does not provide additional parameter-level nuance beyond the schema, matching the baseline for full schema coverage.

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 ('Queue'), a specific resource ('AI press release draft for a track'), and a crucial scoping condition ('owned by the authenticated company'). This clearly distinguishes it from sibling generation tools like droptrack_generate_album_art and droptrack_generate_artist_bio, which target different content types.

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 clearly communicates the trigger context: generating a press release for an owned track. It also provides a concrete next step ('Use droptrack_get_ai_job with jobType=press_release to poll the result'), though it does not explicitly mention alternatives or exclusions.

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