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

With no annotations, the description carries the full behavioral burden. It usefully discloses case-insensitive matching, containment semantics across any cell, and a hard cap of 50 rows, but says nothing about result ordering, what happens on zero matches, truncation behavior when more than 50 rows match, or whether this is a pure read operation.

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 sentence with zero filler, front-loading the resource and scope before the matching rule. It is terse without being cryptic, though the phrasing 'Rows of the Taxooor dataset whose cells contain...' is slightly roundabout.

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 two-parameter read tool with no output schema and no annotations, the description covers the matching contract but leaves the return shape (row objects? ids?), ordering, and edge-case behavior on truncation unspecified. Adequate but with clear gaps an agent would want closed.

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 already documents 'text to look for in any cell' and limit carries min/max constraints. The description restates the any-cell semantics, adds case-insensitivity, and reinforces the 50-row bound, but provides no new syntax or format detail beyond 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 states a specific verb (search) and resource (rows of the Taxooor dataset) and defines the matching rule: cells containing the query, case-insensitive, capped at 50 rows. That is enough to separate it from neighbors like dataset_row or dataset_stats, though it never names those siblings explicitly.

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?

It says what the tool returns but not when to reach for it instead of dataset_top, dataset_row, or dataset_stats. There is no mention of prerequisites, when-not conditions, or alternative tools, so the agent must infer routing from the name alone.

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