preview_table

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

With no annotations, the description must carry the full burden of behavioral disclosure. It mentions 'small sample' but does not explicitly state that the operation is read-only, that the sample may be non-representative, or any performance implications. While the act of 'returning rows' implies non-mutation, important caveats about data shape representativeness are missing.

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, front-loaded with the primary action and purpose. Every sentence earns its place, with no redundant or filler content.

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 with no output schema, the description adequately covers purpose, usage context, and parameter implications. It could be more explicit about the return format, but the mention of 'data shape' sufficiently implies columns and sample rows. Given the tool's simplicity, this is nearly complete.

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 parameters are already well-documented in the schema. The description adds only a general notion of 'small sample' which aligns with the 'limit' parameter but does not provide additional detail beyond what the schema already explains.

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 action ('Return a small sample of rows from a table') and the resource ('table'). It also indicates the purpose ('understand its data shape') and distinguishes it from sibling tools by emphasizing inspection of JSON structures and field formats, setting it apart from query or metadata tools.

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?

It provides clear context for when to use the tool: 'before writing queries' to inspect JSON columns or field formats. However, it does not explicitly state when not to use it or mention alternatives, though the sibling list implies it is a lightweight preview compared to full query tools.

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