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

With no annotations, the description carries the full burden and does disclose two useful traits: matching is case-insensitive and results are truncated at 50 rows. It omits the default value of the optional limit, whether full rows or matched cells are returned, ordering, and any read-only/permission framing.

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?

A single front-loaded sentence with no filler; scope, match semantics, and cap all arrive in one pass. The 'up to 50' clause mildly restates the schema's maximum but also conveys the practical result cap, so it earns its place.

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 search tool with no output schema and no annotations, the description covers matching and the cap but leaves the return shape, default limit, and ordering unspecified. Adequate to call it, not fully 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 coverage is 50%: query is documented but limit has no description, only a max of 50. The description compensates partially by clarifying that the query matches any cell case-insensitively and that output is capped at 50, which is meaningful beyond 'text to look for in any cell', but the limit's default behavior remains unexplained.

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?

It names a concrete verb and resource ('Rows of the Trading Card Value Checker dataset whose cells contain the query') and specifies the matching semantics and result cap, so an agent knows exactly what the tool returns. It does not explicitly distinguish itself from near-siblings like dataset_top or dataset_row, which keeps it shy of a 5.

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?

There is no statement of when to use this versus dataset_top, dataset_row, dataset_compare, or dataset_stats, and no prerequisites or exclusions. Usage is only inferable from the described behavior.

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