sample_table

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

No annotations are provided, so the description must convey behavioral traits. It discloses that the tool returns a random sample, which is a key behavioral fact. However, it does not state that the operation is read-only, discuss potential performance or randomness guarantees, or mention any side effects or constraints. This is a minimal disclosure that leaves the safety profile implicit.

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 a single sentence that is clear and to the point. The core action is front-loaded, and there is no superfluous wording. It is appropriately concise, though it could be slightly more structured with an example, but it doesn't waste tokens.

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?

Given the tool has 5 parameters (1 required) and no output schema, the description is reasonably complete for a straightforward sampling tool. However, it omits the return format or an example invocation, which might leave agents uncertain about the response structure. Since the schema fully documents inputs and the purpose is clear, the gap is minor.

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 description coverage is 100%, meaning every parameter already has an explanation (e.g., count default and max, schema default, server/database fallback). The tool description adds no additional parameter-level context. Since the schema carries the entire burden, the baseline of 3 applies; no extra value is provided here.

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 clearly states the tool's action: 'Get a random sample of rows from a table' and adds context on its purpose ('useful for understanding data patterns'). It differentiates from sibling tools like describe_table and get_table_stats by focusing specifically on sampling rows, which no sibling explicitly offers. The verb and resource are specific and unambiguous.

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 provides only implicit usage context via the phrase 'useful for understanding data patterns.' It does not explicitly state when to use this tool over alternatives like get_table_stats or describe_table, nor does it mention any conditions where this tool should not be used. With many siblings, an agent lacks clear routing guidance.

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