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

With no annotations, the description carries the burden of behavioral disclosure. It usefully states case-insensitive matching and a 50-row cap, but it does not mention result ordering, behavior when no cells match, whether matching is substring-based, or how the optional limit parameter interacts with the cap.

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 packs the dataset name, matching scope, case-insensitivity, and result cap with no filler or redundancy. Key operational detail is front-loaded before the cap limitation.

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 search tool with no output schema, the description is nearly complete: it states what is searched, what is returned, and key matching rules. The main remaining gaps are lack of explicit default for limit and absence of ordering guarantees, but these are minor for a tool this simple.

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 schema describes only the query parameter, leaving the limit parameter undocumented. The description adds useful semantics ('case-insensitive', 'up to 50') but does not explicitly map 'up to 50' to the limit parameter or clarify its default behavior, so it only partially compensates for the 50% schema coverage.

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 identifies the specific verb-resource pair: it searches the Intakez dataset and returns rows containing the query. Its unique focus on text matching in any cell distinguishes it from sibling tools like dataset_row, dataset_stats, or dataset_compare without ambiguity.

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 is implied: use this when you need rows whose cells contain a given text string. However, it gives no explicit guidance about when not to use it or which sibling tool to prefer for other operations (e.g., exact row retrieval with dataset_row or statistics with dataset_stats).

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