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

Annotations already cover safety traits (readOnly, idempotent, non-destructive). The description adds valuable behavioral detail beyond that: it returns up to 10 rows sampled across the dataset rather than the first ten, and returns JSON plus CSV text. It does not cover auth or rate limits, but those are minor for this tool.

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 tight sentences, front-loaded with the return scope and sampling strategy, followed by a direct usage instruction. Every sentence 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 2-parameter read-only tool with full schema coverage and rich annotations, the description covers what an agent needs: output format (JSON + CSV), sampling behavior, and how to present results. No output schema exists, so explaining the return shape here is appropriate and sufficient.

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%, so the baseline is 3. The description adds meaningful semantics for the 'rows' parameter by specifying that the returned rows are spread across the dataset, not just the first ten, which is not captured in the schema.

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 ('get') and resource ('sample rows from the live file') with clear scope (up to 10, spread across dataset). It does not explicitly differentiate from siblings like get_dataset or search_datasets, so it falls short of the top score.

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?

Gives clear usage context: 'Show these to the user so they can judge the fields and quality.' This tells the agent when the tool is useful, but it offers no explicit exclusions or named alternatives for other retrieval tasks.

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