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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context beyond annotations: it specifies that the tool returns entry counts alongside dataset names, and clarifies the semantic of 'datasets' as lookup tables for analyzers. This is useful and not contradictory.

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 two sentences with no fluff. It leads with the action and resource, then immediately clarifies scope and purpose with an example. Every sentence earns its place, and it is appropriately sized for a simple read-only list tool.

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 one-parameter, read-only list tool with full schema coverage and safety annotations, the description is complete. It explains what datasets are, what scope means, and what is returned (datasets with entry counts). No output schema exists, but the return is straightforward and sufficiently described. Nothing critical is missing.

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 100% and the parameter description in the schema already explains the two values ('Either CUSTOMER (the customer's overlay datasets) or GLOBAL (shared by all customers).'). The tool description reiterates this without adding new details, so it provides no value beyond the schema. Baseline 3 is appropriate.

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 ('List') and resource ('well-known datasets') and clarifies scope (CUSTOMER or GLOBAL). It provides an example (disposable_email_domains) that illustrates what datasets are, making it distinct from siblings like list_dataset_entries. However, it does not explicitly name an alternative, so it narrowly misses a 5.

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 implies when to use this tool (when you need the list of datasets and their entry counts) but does not explicitly state when not to use it or mention alternatives. Given the sibling tools, there is a natural alternative (list_dataset_entries) but no guidance is provided to differentiate them in terms of usage context.

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