get_sample_data

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

With no annotations, the description carries the transparency burden. It does disclose useful behavior: the result is capped at 10 rows, filtering is optional, and join_logic combines filters with AND/OR. However, it does not state whether the operation is read-only, what columns are returned, or how errors are handled, leaving some behavioral ambiguity.

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 one-sentence purpose is front-loaded, followed by a compact Args block where each parameter earns its place. There is no redundant or filler text.

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 preview tool, the description covers the essential call mechanics: target table, filter shape, and join behavior. It is a little thin on the output side—no explicit statement of returned columns or empty-result behavior—and it does not mention the sibling run_a_query alternative, but the row cap and filter semantics make the tool usable.

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 has no property descriptions and only 0% coverage, but the description documents all three parameters: table_name, filters (with a concrete JSON format and a value-type warning), and join_logic (with allowed AND/OR values). This fully compensates for the schema's silence.

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 opening line, 'Get sample data (top 10 rows) from a table with optional filters,' names a specific action, a resource (table), and an explicit row cap. This distinguishes it from sibling tools like list_tables and tables_schema, which return metadata, and from run_a_query, which implies a broader query rather than a capped preview.

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 implies a quick-preview use case but never explicitly says when to choose this over run_a_query or how it differs from list_tables/tables_schema. There are no when-to-use or when-not-to-use statements, so an agent must infer tool selection from the name alone.

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