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

Annotations only declare readOnlyHint=true, but the description adds crucial behavioral context: every record is confidence='estimated', dates are derived rather than confirmed, and each record carries its derivation basis. This is exactly the kind of caveat that prevents an agent from misinterpreting the data.

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 tight and well-ordered: a one-line definition, then coverage details, then a critical data-confidence caveat. Every sentence adds value, and the most important caveat is clearly emphasized.

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?

The behavior and data caveats are thoroughly described, and the presence of an output schema covers return structure. However, parameter semantics remain incomplete—particularly 'types' and 'limit'—leaving a noticeable gap for a tool with only three parameters.

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 should compensate, but it only indirectly mentions the entity and event categories. It does not explain the 'types' parameter values, how 'limit' applies, or what format 'entity' should take. The mention of earnings and clinical-trial readouts hints at possible types but is not sufficient for reliable query construction.

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 clearly defines the tool as a forward-looking catalyst calendar for an entity, covering projected earnings dates and clinical trial readouts sorted nearest-first. It specifies the resource and scope, though it does not explicitly contrast itself with sibling tools like get_earnings or get_event_studies.

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 implies usage for future scheduled catalysts via words like 'forward,' 'scheduled ahead,' and 'nearest first,' and it names the two covered event categories. However, it provides no explicit when-to-use/when-not-to-use guidance and does not mention alternative tools for confirmed or past events.

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