check_job_status

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

No annotations are provided, so the description must cover behavioral traits. It mentions possible statuses and a result URL upon completion, adding some transparency. But it does not disclose read-only nature, idempotency, or potential side effects, which are important for a status-checking tool.

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, well-structured with an opening statement, explicit Args and Returns sections, and examples. Every sentence adds value, and the most critical info is front-loaded.

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 has an output schema (though not shown), the description still covers return values (statuses and result URL). It completely explains both parameters, usage scenarios, and provides examples, making it fully adequate for an agent to invoke correctly.

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 0%, but the description adds meaning for both parameters: it describes the format of job_id (UUID example) and explains the endpoint_type enum values with their API associations. This compensates well beyond the schema's minimal type definitions.

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 checks the status of a job, specifying both image generation (Seedream) and editing (Nano Banana). It uses a specific verb 'check' and resource 'job status', and distinguishes from siblings like generate_image and edit_image.

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 explicitly says to use it for monitoring long-running jobs or checking on timed-out jobs. It indicates it works for both endpoints. However, it lacks explicit when-not-to-use guidance or alternative tool referrals, though the examples provide context.

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