get_model_status

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

With no annotations, the description carries the full burden. It implies a non-mutating read via 'Get' and 'persisted', and 'safe failure information' hints at error semantics. However, it does not disclose permissions, side-effect absence beyond implication, or any rate/performance considerations.

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 compact sentence with no filler. It front-loads the verb and resource and adds meaningful qualifiers ('persisted', 'lineage', 'safe failure information') without wasting words.

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?

For a low-complexity one-parameter status tool, the description names the high-level content of the response. But with no output schema, it leaves unspecified the exact return structure, what 'safe failure information' means, and how this differs from get_job_status or archive_model in practical usage.

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?

There is only one parameter, model_id, and schema description coverage is 0%. The description contextualizes the parameter by tying it to 'model fit state', but it does not explicitly explain how model_id is used, what format it takes, or where it comes from. The parameter is self-explanatory enough to partially compensate.

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 ('Get') and names concrete resources: persisted model fit state, lineage, and safe failure information. This distinguishes it from prediction, fitting, and optimization siblings, though it does not explicitly contrast with get_job_status.

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?

No guidance is given for when to use this tool versus alternatives such as get_job_status, archive_model, or the fitting tools. The agent must infer from the name that this is a status/retrieval tool rather than a mutation or prediction tool.

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