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

The description discloses some behavioral traits such as case-insensitivity and the limit cap of 50 rows, which are useful. However, with no annotations present, it does not mention potential side effects, permissions, or error behavior, leaving some transparency gaps.

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 concise sentence that conveys the core functionality and key constraints without extraneous details. 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?

Given the simple schema (two parameters, no output schema), the description covers the main purpose and critical behavior. It could mention return format or error handling, but these are not essential for understanding basic usage.

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 description clarifies the meaning of both parameters: 'query' is matched case-insensitively in any cell, and 'limit' sets a maximum of 50 results. This adds semantic value beyond the sparse schema descriptions, though the limit parameter lacks an explicit description in the schema.

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 function: it returns rows from the Tickmarko dataset based on a case-insensitive substring match across all cells. This is specific and unambiguous, distinguishing it as a full-text search operation.

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?

No guidance is provided regarding when to use this tool instead of the sibling tools (e.g., dataset_row, dataset_stats, dataset_top). There is no mention of use cases, limitations, or alternative scenarios.

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