mlflow_experiments_list

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

The description adds the REST endpoint URL but does not disclose any behavioral traits beyond what the readOnlyHint annotation already provides. The annotation already signals this is a safe read operation, so the description adds minimal value. No contradictions.

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 extremely concise, a single sentence. It is front-loaded with the core purpose. However, it could include a bit more context without becoming verbose, so not quite a 5.

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?

The description is severely incomplete given the tool's 5 parameters (filter, pagination, ordering) and the presence of an output schema. Critical usage details like how to filter, handle pagination, and interpret results are missing. The agent cannot effectively use this tool based solely on the description.

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 only 20% (only view_type is described in schema). The tool description does not mention any parameters or their purposes, failing to compensate for the low schema coverage. The agent receives no guidance on how to use filter, order_by, page_token, etc.

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 indicates the verb 'Search' and resource 'experiments', and mentions the REST endpoint. It distinguishes itself from sibling tools like create/delete/get/update by specifying a search operation. However, it does not elaborate on the scope or filters beyond the basic verb.

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 like mlflow_experiments_get for a specific experiment or mlflow_runs_search for runs. There is no mention of prerequisites or typical scenarios.

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