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

Annotations already indicate read-only, idempotent, and non-destructive. The description adds valuable behavioral context: no authentication required, the exact return shape with fields like metadata.publisher (clarifying that it's the account that published, not the source), and guidance to cite by url. This exceeds what annotations provide and has 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 well-organized: it leads with the core purpose, gives an example, explains the return structure, and notes alternatives. Every sentence adds value; no fluff or repetition. It is appropriately sized for the tool's simplicity.

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?

With no output schema, the description fully covers the return format (id, title, text, url, metadata with subfields). It also covers authentication (none needed), the input format, and routing to related tools. Nothing essential 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?

The schema only defines 'id' as a string with length constraints, and schema description coverage is 0%. The description compensates by explaining that the id is a slug from search and that a canonical dataset URL also works, adding meaning beyond the schema's minimal definition.

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 (fetch) and resource (full public document for a dataset as Markdown) and clearly distinguishes itself from siblings by naming get_dataset and get_table_schema for machine-readable table ids and schemas. 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?

It explicitly says 'No account needed,' provides an example with a slug, and notes that a canonical dataset URL also works. It also states when to use alternatives (get_dataset and get_table_schema) for machine-readable data, making usage guidance explicit.

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