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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only the 'current tenant' scoping detail; it says nothing about whether the name must be unique, what happens on a duplicate name, required permissions, or what the call returns (there is no 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?

A single front-loaded sentence with no filler or redundancy. Its brevity is appropriate in form but reflects under-specification rather than disciplined economy.

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 mutation tool with four parameters, no output schema and no annotation coverage of return behavior, the definition should say what is created and what identifier comes back so the agent can chain into dataset_item_add or dataset_get. That information is absent, as is any note on name conflicts.

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 coverage is 75%, with name, nodeId and workflowId documented in the schema while the 'description' parameter has no description at all. The tool description adds no meaning beyond the schema — it does not explain what nodeId or workflowId bind the dataset to, which is the non-obvious part of the signature.

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?

States a specific verb and resource ('Create an evaluation dataset') and its tenant scope, which distinguishes it from dataset_get, dataset_list, dataset_update and dataset_delete among the siblings. It stops short of explicitly naming an alternative, so it is clear but not fully differentiated.

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?

There is no guidance on when to use this versus dataset_update or dataset_item_add, no prerequisites, and no note on how datasets relate to judges or experiments (llm_judge_create, experiment_request_trial). The agent must infer all usage context from the name alone.

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