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

Annotations already declare readOnly and idempotent, but the description adds critical behavioral context: the expected statuses, polling interval, and how to handle pending vs. complete states. This goes well beyond the structured annotations and gives the agent a complete mental model of the tool's 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?

The description is compact (~50 words) and front-loaded with the primary purpose. Every sentence adds actionable information: purpose, polling guidance, response handling, and an example. No redundant or filler 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?

Given the tool's simplicity (one parameter, output schema available), the description is remarkably complete. It covers purpose, how to poll, what to look for, how to respond to pending work, and how to handle results, leaving no ambiguity for an agent.

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 already documents job_id with a description, and coverage is 100%. The description adds value by specifying which tools produce the job_id and providing a concrete URL example, clarifying the origin and format of the parameter beyond the schema alone.

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: 'Get the status or result of a job started by deep_research, translate_pdf, or make_slides.' This clearly identifies the tool's function and distinguishes it from sibling tools like check_grammar and translation utilities, which serve different purposes.

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?

It explicitly explains when to use the tool (after starting a job with specific tools) and provides detailed polling instructions: 'Poll every 15-30 seconds until status is "done" or "error"'. It also guides follow-up actions with retry_after_seconds, next_action, and structured_result, making usage clear.

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