get_table_sample

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

With no annotations, the description carries the burden of behavioral disclosure. It adds the useful constraint of max 20 rows and cross-database notation, but does not state whether the operation is read-only, how the sample is selected (e.g., random vs first rows), or any error behavior. This is adequate for a simple fetch but leaves gaps.

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 two sentences, with the main purpose front-loaded and no filler. Every phrase adds value, and it remains concise while conveying the essential behavior.

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's simplicity and the presence of an output schema, the description covers the core functionality. It misses key context such as usage guidance vs siblings, the read-only nature, and semantics of the limit parameter. Completeness is adequate but not thorough.

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 0%, so the description must compensate. It adds meaning to table_name by noting database.table notation, and implies a limit parameter by stating max 20. However, it does not explicitly explain the limit parameter's role or default, so the compensation is partial.

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 fetches a representative sample of rows with a max of 20 from a table, distinguishing it from the sibling tools execute_sql and get_schema_info. The verb 'fetch' and resource 'sample from a table' 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?

No explicit guidance on when to use this tool versus the siblings. It does not mention that execute_sql is for arbitrary queries or that get_schema_info is for metadata. The only usage hint is the database.table notation, which is a parameter detail, not a when-to-use instruction.

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