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

No annotations are provided, so the description carries the full burden. It discloses that browsing is free and that record counts are included, but doesn't mention output structure, pagination, or any potential side effects. For a zero-parameter list tool, this is adequate but minimal.

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?

Two sentences, front-loaded with the core purpose. The second sentence adds relevant examples without redundancy. Every word earns its place.

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 simple list tool with no parameters and no output schema, the description is reasonably complete. It includes dataset categories and cost indication. It could mention return format or next steps, but those aren't essential for this straightforward tool.

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 input schema is empty, so schema coverage is 100% with zero parameters. The description correctly omits parameter details since none exist. Baseline 4 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 'List all available datasets with record counts' — a specific verb, resource, and output detail. It clearly distinguishes from sibling tools like 'fetch_dataset' (which fetches a specific dataset) and 'list_products' (which lists products, not datasets).

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 phrase 'Free to browse' gives clear context for when to use the tool (browsing datasets without cost). The listed data categories (market ticks, DePIN stats, etc.) imply exploration use cases. It doesn't explicitly state exclusions or compare to alternatives, but the context is clear enough.

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