get_inference_run

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'status and results' but lacks detail on what constitutes results (e.g., final vs. intermediate), error states, or whether the tool can be called multiple times. Minimal behavioral context.

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 a single sentence with no superfluous words. However, it is overly terse and could benefit from slight expansion to cover key points without losing conciseness.

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 explained. The tool has one required parameter and is read-only. The description is minimally adequate but omits context like whether results are immediate or require polling, and any special conditions for status values.

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 has one parameter 'run_id' with no description. The tool description does not explain the parameter's format, constraints, or typical values (e.g., where to find the ID). With 0% schema coverage, the description should compensate but fails to add meaning.

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 retrieves both status and results of an inference run. This distinguishes it from sibling tools like 'run_inference' (creates a run) and 'list_inference_runs' (lists runs).

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 implies usage for checking a specific run's outcome but does not explicitly exclude other scenarios or compare with alternatives like 'list_inference_runs' for overviews or 'run_inference' for new runs.

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