auto_annotate_status

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

The description goes well beyond the readOnly and non-destructive annotations by fully explaining the semantics of activeJob and lastRun, including null behavior, in-flight progress, failure/stopped flags, results, and error representation. This gives the agent a clear model of what the response means without needing an output schema.

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 two sentences with no filler. The first sentence front-loads the tool's purpose and accepted input forms, and the second sentence delivers essential return-value semantics. Every sentence contributes useful information.

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?

Despite having no output schema, the description fully explains the observable return behavior: both fields null means no run yet, activeJob shows in-flight progress, and lastRun captures results or errors. Together with the read-only annotations and single fully documented parameter, this is complete enough for correct invocation and interpretation.

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%, and the main description repeats the exact acceptable dataset reference forms already present in the schema: slug, owner/slug, or ul://owner/datasets/slug URI. Therefore, the description adds no new parameter meaning beyond the schema, so the baseline score of 3 is appropriate.

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 uses a specific verb and resource: 'Get an auto-annotation run's status for a dataset.' It clearly identifies the target as a status-checking operation rather than a starting or stopping operation, distinguishing it from the sibling tools auto_annotate_start and auto_annotate_stop. The supported dataset reference forms are also stated.

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 the tool is for checking auto-annotation run status, but it does not explicitly state when to use it versus alternatives, nor does it mention exclusions such as 'use auto_annotate_start to begin a run.' The purpose is clear enough that an agent can infer the usage context, but explicit routing guidance is absent.

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