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

With no annotations, the description carries the full behavioral burden. It does disclose key behavior: case-insensitive substring matching, search across all cells, and a result cap of 50 rows. It does not mention sorting, pagination, or what happens when more than 50 rows match, but for a simple search tool these omissions are minor.

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, efficient sentence with no filler. It front-loads the core operation and embeds the most important constraints (case-insensitivity, result cap). Every word contributes to 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?

For a tool with only two parameters and no output schema, the description provides the essential context: what is searched, how matching works, and the maximum result count. The main missing piece is the exact shape of returned rows and default behavior when limit is omitted, but an agent can likely infer these from the dataset context and sibling tool names.

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 50%: query is documented in the schema, but limit is not. The description adds semantic value by relating the 'up to 50' cap directly to the limit parameter and clarifying that matching is case-insensitive across any cell. This partially compensates for the missing schema description of limit.

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 rows of the dataset whose cells contain the query, with case-insensitive matching. It distinguishes the tool from siblings like dataset_row or dataset_stats by focusing on search behavior across all cells. The resource and verb 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?

The context is clear: use this tool when you need to find dataset rows matching arbitrary cell content. However, it does not explicitly mention when not to use it or call out alternatives such as dataset_row for row-by-ID retrieval or dataset_top for highest-ranked rows. The implied usage is still strong.

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