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

With no annotations provided, the description discloses important behavioral details: case-insensitive matching, cell containment semantics, and a result cap of 50. It does not mention default limit behavior, sorting, or whether it is read-only, but the core behavior is transparent.

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, focused sentence that communicates the essential behavior with no unnecessary words. It is well-structured and easy to parse.

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 search tool with no output schema or annotations, the description covers the main purpose, matching behavior, case sensitivity, and result limit. It lacks details like default limit or sorting order, but these are not critical for the agent to understand and use the tool effectively.

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 query parameter is described in the schema, and the description adds case-insensitivity. The limit parameter is not described in the schema, but the description clarifies the maximum result size with 'up to 50'. This adds meaningful context beyond the schema, though the default limit is not specified.

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 that the tool returns rows from the TakeoffDeck dataset where any cell contains the query, with case-insensitive matching and a limit of 50. This distinguishes it from the sibling tools like dataset_columns, dataset_stats, or dataset_top by focusing on row-level content search.

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 explains what the tool does but does not explicitly say when to use it compared to the sibling tools. It implies usage for content-based row lookup, but it does not name alternatives or provide selection criteria.

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