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

With no annotations, the description carries the full burden. It does add genuine behavioral facts (case-insensitive matching, a hard cap of 50 rows), which is useful. However, it omits return shape, whether results are truncated silently at 50, and any auth or pagination semantics needed 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 front-loaded sentence that names the resource, the matching rule, and the cap with no wasted words.

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 with no output schema, the description conveys what matches and the cap, but does not describe the columns returned or result ordering, which matters given there is no output schema to fall back on.

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 as 'text to look for in any cell', but limit is undocumented in the schema. The description partially compensates by clarifying case-insensitivity and the 50-row maximum, though it never explains the limit parameter's meaning or default, leaving a real gap.

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 concrete operation on a concrete resource: returning rows of the Commercial Refinance Quotes dataset whose cells contain the query. It is clear what the tool returns, but it does not distinguish itself from siblings like dataset_row, dataset_top, or dataset_stats, so the 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?

There is no explicit when-to-use guidance and no named alternatives among the sibling tools. The agent is left to infer that this is the free-text lookup vs. dataset_top or dataset_row, but nothing in the text says so.

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