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

The description discloses the optimistic concurrency behavior (reads current version and refuses concurrent changes) and the side-effect-free nature ('metadata only'), which are not captured in the annotations. The annotations only state idempotentHint=true and destructiveHint=false, but the description adds critical behavioral details about precondition handling and that no rebuild occurs. No contradiction with 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 focused paragraph that front-loads the purpose, then provides an example, return format, and key constraints. Every sentence contributes value: the concurrency note, the metadata-only clarification, and the uniqueness rule are all essential. There is no fluff or redundancy.

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 3-parameter tool with no output schema, the description covers everything an agent needs: the action, the exact parameters via example, the return object, the concurrency behavior, the uniqueness constraint, and the side-effect-free nature. The absence of an output schema is compensated by the explicit return format. Nothing critical is missing for correct invocation.

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 0%, so the description must compensate. It clarifies that 'name' and 'description' are the editable fields and that 'dataset_id' identifies the dataset. The example provides a concrete usage, and the uniqueness constraint on 'name' adds semantic meaning beyond the schema's simple string type. While it doesn't detail every parameter's format, the schema already provides type and length constraints, and the description covers purpose.

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 a specific verb ('Changes') with a clear resource ('a dataset's display name, its description, or both'). It explicitly distinguishes this as a metadata-only update, which separates it from sibling tools like create_dataset or query_table. The purpose is unambiguous and 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?

The description provides clear context for when to use this tool: it is for metadata updates only, explicitly noting 'Nothing rebuilds.' It also implies it applies to existing datasets and mentions the uniqueness constraint on names. However, it does not explicitly name alternative tools for other operations, though the metadata-only boundary is a strong usage guideline.

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