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

Annotations already declare readOnly, openWorld, and idempotent behavior. The description adds valuable context not in annotations: searches are logged for demand analysis, and a found tool may require reconnecting. It doesn't describe the return format, but that is less critical for a discovery 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?

Four sentences, each contributing information: purpose, logging note, alternative tool, and usage caveats. Front-loaded with the core action. Efficient though slightly longer than strictly necessary.

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 discovery tool with one parameter, no output schema, and rich annotations, the description covers purpose, alternatives, logging behavior, and reconnection caveats. It could clarify the response format (e.g., list of datasets with tool names), but overall it gives enough for correct invocation.

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 100% for the single query parameter, with a detailed description and examples. The description adds no additional parameter semantics beyond what the schema already provides, so baseline 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?

States a specific verb ('Find'), resource ('relevant LiveDataLink datasets and exact tool names'), and input ('plain-language data request'). It explicitly distinguishes itself from the sibling list_tool_groups, so an agent can tell them apart without inspecting schemas.

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?

Names an alternative (list_tool_groups) and the condition for using it, and adds caveats about reconnecting and checking freshness. It lacks an explicit 'when not to use' statement, but the context is clear.

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