get_job_result
Status of a job started by a generate_* tool; when complete, the download URLs (they carry the key).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | ||
| api_key | Yes |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Status of a job started by a generate_* tool; when complete, the download URLs (they carry the key).
| Name | Required | Description | Default |
|---|---|---|---|
| job_id | Yes | ||
| api_key | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, so the safety profile is covered. The description adds that completed jobs expose download URLs, which is useful, but it says nothing about pending/failed states, result expiry, or what the trailing remark about the key means.
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?
It is a single front-loaded sentence with no filler. The parenthetical about the key is the only awkward element, reading as an afterthought rather than a clear statement.
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?
An output schema exists, so return values need not be described, and annotations cover safety. What is missing for a polling tool is lifecycle guidance: intermediate states, failure handling, and retrieval cadence, which an agent needs to use it 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 description coverage is 0%, so the description must carry the parameter burden, and it largely does not. The job_id comes implicitly from a generate_* tool, but neither parameter is explained, and 'they carry the key' is too cryptic to clarify why api_key is required separately.
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 names a specific resource and action: it reports the status of a job that was started by a generate_* tool, and it says download URLs appear on completion. The reference to the generate_* family distinguishes it from siblings such as get_design_conditions or list_cmip6_models.
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?
Usage is implied rather than stated: an agent infers it should call this after a generate_* tool returns a job id. There is no explicit guidance on when to stop polling, how often to poll, or what to do if the job fails.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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