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

No annotations are provided, so the description carries the full behavioral burden. It discloses two useful traits: case-insensitive matching and a 50-row cap. However, it does not describe the return structure or edge-case behavior (e.g., empty result handling), and the read-only nature is only implied by 'search' rather than stated. This is serviceable but leaves gaps for a tool with zero annotation coverage.

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 tight sentence with zero filler—the action, scope, matching rule, and cap are packed into one line. All information is front-loaded and every word contributes meaning. There is nothing extraneous to trim.

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 and no annotations, the description covers the core search behavior, case sensitivity, and row cap. Still, the absence of an output schema means the return format is unspecified, and the read-only/safety profile is unstated given no annotations. It is adequate but not fully complete for an agent that must infer response shape.

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% (only 'query' has a description; 'limit' does not), so the description partially compensates by binding 'cells contain the query' to the query parameter and 'up to 50' to limit. It adds the case-insensitivity detail absent from the schema, which is genuine value. It does not, however, elaborate on limit semantics beyond the redundancy with the schema's maximum.

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 names a specific verb and resource ('Rows of the Background Check Quotes dataset') with concrete behavior: cells containing the query, case-insensitive, capped at 50. This is clear and actionable. It falls just short of a 5 because it doesn't explicitly contrast with siblings like dataset_row or dataset_top, though the 'any cell' matching behavior implicitly distinguishes it from column-level and row-by-id lookups.

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 intended use case—searching any cell for a query string—is clearly implied by the description, but there is no explicit mention of alternatives or when-not-to-use guidance. With siblings like dataset_row, dataset_top, dataset_compare, and dataset_provenance present, an agent might benefit from routing hints, but the description's 'any cell' wording conveys the primary scenario adequately without naming exclusions.

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