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

Annotations declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds operational behavior not covered by annotations: polling frequency, response fields like retry_after_seconds and next_action, and preference for structured_result. It also includes a concrete example URL, making the tool's behavior very transparent.

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 concise and front-loaded: the first sentence states the core purpose, the second gives actionable polling and handling instructions, and the final example URL is a compact illustration. Every sentence contributes, with no redundant content.

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 tool with one required parameter, an output schema, and strong annotations, the description covers purpose, usage, and behavioral details. It explains the job lifecycle (pending vs. complete) and how to respond, making it complete for the tool's complexity and context.

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 fully describes the only parameter (job_id) with 100% coverage. The description adds value by indicating the job_id originates from specific job-starting tools ('job started by deep_research, translate_pdf, or make_slides') and showing its use in the example URL. This enhances understanding beyond the schema, though not excessively.

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 clearly states the tool's function: 'Get the status or result of a job started by deep_research, translate_pdf, or make_slides.' It uses a specific verb and resource, and names the sibling tools that initiate jobs, distinguishing it from those tools.

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 provides explicit usage guidance: it names the exact tools that start the jobs to check, gives a polling interval ('Poll every 15-30 seconds'), and describes how to handle pending vs. complete states ('follow retry_after_seconds and next_action', 'prefer structured_result'). This goes well beyond basic intent.

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