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

Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds meaningful behavioral context: it's market-wide (not company-specific), and it details the three kinds and their aliases, clarifying what each returns (e.g., holidays, open status, IPO pipeline). It does not describe pagination or errors, but for a read-only tool with an output schema, this is adequate.

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 concise and well-structured. It opens with a one-line summary, then uses a bulleted list to explain the kinds, and ends with a sibling alternative. Every sentence serves a purpose, and the most critical information is front-loaded.

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?

Given the output schema is present and annotations cover read-only safety, the description is complete for an agent to call the tool correctly. It explains the three kinds, the optional date parameter for status, and directs to get_calendar when relevant. No critical information is missing for successful 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 description coverage is 0%, so the description must explain parameters. It thoroughly explains the 'kind' parameter with aliases and what each selects, and mentions that 'date' optionally applies to status. The 'limit' parameter is not explained, but it is a common and self-explanatory integer. The description compensates well for the schema's lack of documentation, especially for the most important parameter.

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 states the tool provides market-wide reference data and enumerates three distinct kinds (calendar, status, IPO) with their meanings. It explicitly differentiates from get_calendar for company-specific data, so an agent can immediately identify scope and purpose.

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 guidance on when to use this tool versus get_calendar: 'For one company's earnings/event calendar, use get_calendar.' It also explains what each kind returns, providing clear context for selecting the appropriate kind. No ambiguity about when to invoke it.

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