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

Annotations cover idempotency and non-destructiveness, but the description adds substantial context: asynchronous return with a job ID, the need to poll get_studio_job, local-model-only operation with no external AI fallback, and the consent requirement for nonconfidential content. This goes well beyond what the annotations state.

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 front-loaded with purpose and task types, then proceeds through required inputs, return behavior, and polling instructions. Every sentence carries actionable information with no redundant restatement of the schema.

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 asynchronous job submission tool with no output schema, the description covers what the agent must know: the immediate return is a job ID, subsequent polling uses get_studio_job, and the local-model/no-fallback constraint is disclosed. Combined with the schema details for messages and limits, nothing material 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?

Schema coverage is 75%, so the schema already documents most parameters. The description adds useful semantics beyond the schema: consent is specifically for 'nonconfidential permitted content' and the idempotency key should be 'stable' for retry safety. The access_token parameter is not mentioned in the description, leaving one gap.

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 action ('queue a free text task') and enumerates the task types (draft, summarize, extract, translate, reason, code assistance). It distinguishes itself from the compute/image siblings through 'free text' and 'No code is executed', making the resource and scope unambiguous.

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 task list gives clear context for when this tool applies, and it explicitly routes the agent to get_studio_job for polling. The implicit exclusion of actual code execution ('No code is executed') helps, but it does not name submit_compute_job or submit_image_job as alternatives for those cases, leaving some inference to the agent.

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