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

Annotations already declare a non-read-only, non-idempotent, non-destructive, open-world write, so the safety profile is covered. The description adds genuinely new context by stating this is an async job ('A job, like kling_omni_image') and giving the endpoint, which implies a task id must be polled via kling_get_task. It stops short of naming the polling tool or the returned job id field, but it adds real value beyond the annotations.

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?

Three short sentences, front-loaded with the scoping rule and the alternative before any incidental detail. The trailing 'POST /images/upscale' line is marginal for an agent that invokes via tool call rather than raw HTTP, but it costs little.

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?

There is no output schema, so the description carries some return-value burden, and 'A job, like kling_omni_image' does convey that an async job is produced. For a 3-parameter tool with full schema coverage and annotations covering safety, this is nearly complete; only the polling follow-up (kling_get_task) is left implicit.

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 description coverage is 100%, so each parameter is already documented in the schema (email, workId, task_id). The description restates the task_id + workId pairing and the same-account rule but adds no format, syntax, or edge-case detail beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb (upscale), a specific resource (one image of a finished Kling image task), and the exact inputs that identify it (task_id + its workId, same account). It explicitly names the sibling kling_enhance_image as the tool for any other image, so an agent can distinguish it without opening either schema.

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 routing rule is explicit: use this tool only for a finished Kling image task, and use kling_enhance_image for any other image. The 'same account' constraint further narrows applicability. Both the use case and the exclusion are stated, leaving nothing to inference.

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