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 that matching is case-insensitive and that results are capped at 50, but says nothing about truncation behavior when more rows match, result ordering, or the returned column shape — significant gaps for a search tool.

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 no filler, and the most important information (what is matched, and the cap) is front-loaded. Nothing needs trimming.

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-only search with no output schema, the description is minimally adequate but leaves open what happens on truncation, whether results are ordered, and what fields come back. An agent could call it correctly, but not predict the result set.

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 in the schema, while 'limit' has no schema description. The description adds 'case-insensitive' on top of 'text to look for in any cell', which is genuine added meaning, but the limit parameter's purpose (truncating/controlling result count) is only obliquely implied by 'up to 50'.

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?

States a specific verb and resource combination: rows of the FlightDelayHQ dataset matching a cell query, with the match semantics (case-insensitive, any cell) baked in. It is clear on its own, but it never distinguishes itself from siblings like dataset_row, dataset_top, dataset_compare, or dataset_stats, so an agent must infer the boundary.

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?

Usage is only implied by the stated match semantics ('cells contain the query'), which suggests full-text scanning rather than filtered/aggregate retrieval. No explicit when-to-use, when-not-to-use, or named alternative (e.g., dataset_top or dataset_stats) is given, so the agent must infer routing from sibling names alone.

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