sample_rows

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

No annotations are provided, so the description carries the full burden. Sampling implies a read-only, non-destructive operation, but the description never states that explicitly, nor does it mention the 50-row cap or any access requirements. It adds genuine context about why one samples (missing-value encodings, field formats), which lifts it above a bare minimum.

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 with zero waste; the action is front-loaded and the rationale follows immediately. Nothing is padded or repeated from the schema.

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?

An output schema exists, so return values need no explanation, and all four parameters are documented in the schema. The description covers purpose and use context adequately; only the read-only/safety framing and routing against siblings are absent, which is a minor gap for a low-risk sampling 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?

Schema description coverage is 100%, so the schema already documents schema, table, columns and limit (including the 1-50 bounds and the advice to specify columns on wide tables). The description adds no parameter-level syntax or format detail beyond that, so the baseline 3 applies.

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+resource: sample a few real rows from a table, and goes further by naming the goal (confirming value shapes, missing-value codes like 96/97/98/99, field formats). This is far more concrete than a bare 'sample_rows' restatement, though it does not explicitly contrast itself with run_query or describe_table.

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 a clear use context — use it to verify how values are actually encoded and formatted, especially sentinel missing-value codes. It does not name alternatives (e.g. run_query for filtered pulls, describe_table for schema-only inspection) or state when-not-to-use, so it stops short of the top band.

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