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

With no annotations, the description carries the behavioral disclosure burden. It adds meaningful behavior: matches are case-insensitive and results are capped at 50 rows. It does not mention ordering or pagination, but for a simple read-oriented search these are not critical omissions.

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, tightly worded sentence that front-loads the core capability and includes key constraints. Every element earns its place with no filler.

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 two-parameter search tool with no output schema, the description provides the essentials: what is searched, how matching works, and the result cap. It could mention result ordering or behavior on empty matches, but these are minor and not necessary for correct invocation.

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%: the query parameter is documented, while limit only has type/min/max without a description. The description partially clarifies limit by stating 'up to 50', but does not specify how the limit parameter interacts with the default or user-specified cap. It adds some value but doesn't fully compensate for the gap on 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 that the tool returns rows of the Ppmly dataset containing the query in any cell, with case-insensitivity and a cap of 50. This is a specific verb/resource pairing that distinguishes it from siblings like dataset_columns, dataset_stats, and dataset_top.

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 the tool should be used when you need to find rows by free-text cell content, but it does not explicitly state when to prefer it over siblings or mention exclusions. It provides functional context but leaves alternative selection to inference.

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