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

Annotations already mark it read-only, idempotent, and open-world, and the description adds valuable behavioral details beyond that: it costs no credits, it logs every search to a roadmap database, and it returns only tool names rather than data. It also notes that new domains are reviewed based on observed requests, matching the openWorldHint. No contradiction with annotations.

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?

The description is front-loaded with purpose and usage, but it becomes a long wall of text enumerating dozens of data domains. While this catalog listing is informative for a discovery tool, it could be trimmed or structured more tightly; the pricing URL and repeated 'data' phrasing add some bloat. It earns a mid score for being useful but not concise.

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 single-parameter discovery tool with no output schema, the description covers what an agent needs: when to call it, what it returns (exact tool names), cost behavior (free/no credits), side effects (logging to roadmap), and the recommended follow-up action. The breadth of domain examples also helps the agent judge whether this tool can answer a given data-coverage question.

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 single query parameter is already fully documented in the input schema with type, length constraints, and examples ('trucking safety', 'stock prices'). The description reinforces what the query should be but does not add meaningful semantic detail beyond the schema, so the baseline of 3 is appropriate.

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 opens with a clear verb and resource: search LiveDataLink's entire data catalog. It explicitly states the output ('returns exact tool names for matched domains') and positions itself as the discovery/routing tool, distinguishing it from the many data-specific sibling tools. An agent can immediately tell this is not a data-retrieval tool.

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 description gives explicit usage triggers: call FIRST when unsure which tool to use, when the user asks about data availability, and lists concrete example queries. It also names the next step after finding a tool (get_free_api_key). It does not explicitly state when not to use it, but the 'FIRST' directive and trigger examples make the intended context clear.

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