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

With no annotations provided, the description carries the full burden, and it delivers: discloses return structure (lean summaries, relevance score, matched fields, dimension_matches list), acronym matching behavior, which short acronyms are recognized, and the result-limiting behavior. This is rich behavioral context beyond what schema or annotations would show.

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 dense paragraph with zero filler: purpose is front-loaded, followed by return details, acronym edge behavior, next-step guidance, and limit semantics. Every sentence earns its place.

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 tool that already has an output schema, the description covers the discovery context, when to use it, what to do next, return details, acronym edge cases, and limit behavior. Nothing needed for correct invocation or interpretation is missing.

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 description coverage is 0%, so the description must explain the parameters. It does: 'query' is defined as keyword search across catalog metadata with a dimension example, and 'limit' is explicitly described as capping results with default 20 and max 100. This adds meaning far beyond the bare schema names and types.

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 ('search'), resource ('catalog metadata'), and explicitly lists the fields searched (topic names, descriptions, tags, AND column names/descriptions). Positions itself as 'the discovery entry point when you don't know the exact topic name,' which clearly distinguishes it from describe_dataset and other siblings.

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?

Provides a clear condition for use ('when you don't know the exact topic name') and a follow-up instruction ('Follow up with describe_dataset'). While it doesn't explicitly name an alternative or say 'don't use this when you know the exact name,' the guidance implies it strongly.

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