db.sample_values

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

With no annotations, the description carries the burden of disclosing behavior. It reveals that values are distinct and non-null, which is useful, but it does not mention whether sampling is random, how ordering works, what happens for columns with no non-null values, or if database parameter is required. The behavior is partially transparent but not comprehensive.

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 grammatically clear and front-loaded with the main verb. It is concise and free of fluff, but it could benefit from additional structural elements like examples or parameter explanations to aid understanding.

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?

This tool has 4 parameters, no output schema, and no annotations. The description is too brief to convey the expected return structure (e.g., mapping of column to sample values), edge cases, or the role of the 'database' parameter. It is not complete enough for an agent to correctly invoke this tool without additional inference.

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%, and the description does not explain the 'limit' or 'database' parameters. It only hints at 'columns' via 'selected columns'. The description fails to compensate for the lack of schema descriptions, leaving two parameters semantically unexplained.

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 uses a specific verb ('Return') and clearly identifies the resource ('small distinct non-null sample values for selected columns in a table'). It distinguishes this tool from siblings like db.query (full query execution) and db.preview (likely raw row preview) by emphasizing sampling of distinct non-null values per column.

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 implied usage is to explore actual data values in columns, but there is no explicit statement about when to use this over alternatives (e.g., db.preview, db.query). No exclusions or alternative tool names are mentioned, so guidance is only implicit.

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