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

The description clearly conveys asynchronous behavior ('Queue... Poll with droptrack_get_ai_job') and provides the exact polling contract via jobType=artist_bio. It also scopes the operation to the authenticated company, adding meaningful context beyond the annotations, which only indicate readOnlyHint=false and destructiveHint=false.

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 no filler: the first states the action, the second gives the essential follow-up step. The most important information is front-loaded and every sentence 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 no-parameter async job-queueing tool with an output schema present, the description is fully complete. It tells the agent what the tool does, the scope, and exactly how to retrieve the result via droptrack_get_ai_job, so no critical information 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 input schema has zero parameters, so there are no parameter details to document. The description adds implicit-context meaning by noting that the operation applies to the authenticated company, which is the relevant contextual input for this tool.

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 uses a specific verb, 'Queue', and a clear resource, 'an AI artist bio draft', scoped to 'the authenticated company'. It is easily distinguished from sibling generation tools like droptrack_generate_album_art and droptrack_generate_press_release because the target artifact is explicitly an artist bio.

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 states exactly what action to take after invoking this tool: poll droptrack_get_ai_job with jobType=artist_bio. It clearly implies this tool is the right entry point for generating a bio draft, though it does not explicitly list alternatives or when not to use it.

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