mlflow_model_versions_update

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

The annotations already indicate a write operation (readOnlyHint=false). The description adds no additional behavioral context such as idempotency, side effects, permissions, or what happens on success/failure. Thus, it provides minimal added value beyond 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?

The description is a single sentence, which is concise but at the expense of completeness. It lacks structure and front-loads minimal info. While not verbose, it sacrifices content for brevity.

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?

Given the tool has an output schema (not detailed) and multiple siblings, the description fails to explain what the update does (e.g., only updates description?) or what the return value is. It is incomplete for an LLM to reliably understand the tool's behavior.

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 schema has 67% description coverage, but the description itself mentions no parameters or adds extra meaning. It does not clarify the optional 'description' parameter or any constraints. With high coverage, baseline is 3, but the description offers zero parameter information, warranting a lower score.

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 states 'Update a model version' which clearly communicates the verb and resource. It distinguishes from sibling tools like create, delete, get, list, and transition_stage. However, it lacks specificity on which fields are updatable, which is evident from the schema but not reinforced in the description.

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 provided on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context for updating a model version. Sibling tools like mlflow_model_versions_transition_stage or mlflow_registered_models_update are not compared.

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