top_rows

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states sorting is descending, which is good, but doesn't mention whether ties are handled, if the tool modifies the dataset (likely no, but not stated), permissions needed, performance implications for large datasets, or what happens if the column doesn't exist. For a data query tool, the lack of safety/read-only indication is a gap.

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 extremely concise: one sentence for the purpose, then a bullet-like Args section. Every line adds value, no filler or redundancy. It's also front-loaded with the main action.

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 an output schema (context signal), the description doesn't need to explain return values. It is relatively complete for a simple query tool: states the sorting direction, documents all params, and provides a default. The only missing context is behavioral specifics (e.g., read-only, error handling) and tie-breaking, but these are secondary for a straightforward sorted row retrieval.

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 does so by clearly documenting each parameter: 'name: the dataset name', 'column: the column to sort by', 'n: how many rows to return (default 5).' This adds semantic meaning beyond the schema's minimal 'Name' and 'Column' titles, including the default value for 'n'.

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 purpose: 'Return the top-N rows sorted by column descending.' This uses a specific verb (Return) and resource (top-N rows) with sorting direction clarified, which distinguishes it from siblings like 'filter_rows' (which filters, not sorts) and 'summary' (which aggregates). However, it doesn't explicitly contrast itself against these siblings in the description.

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 usage via the Args section, indicating when each parameter is needed. However, it provides no explicit guidance on when to use this tool vs alternatives like 'filter_rows' for row selection or 'summary' for statistical overviews. The sibling tools suggest a data exploration workflow, so a brief note on context would help.

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