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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly explains the payment flow: call without x_payment to receive terms, then call again with x_payment to get data. It also describes what each view does, including that 'is_open' explains why a market is closed. While it doesn't mention rate limits or output format, the payment mechanism and view semantics are well disclosed.

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 dense but not bloated; every sentence adds necessary information. The views are listed in a compact semicolon-separated manner, and the payment instructions are concise. It is front-loaded with the main purpose, but the payment callout could be slightly better structured. Overall, it earns its length.

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 tool's complexity (8 parameters, no output schema, no annotations), the description covers the essential behavioral aspects: all view modes, the payment workflow, and a pointer to the free pricing alternative. While it doesn't explicitly describe return formats or error handling, it provides enough context for an agent to select and invoke the tool for most calendar-related queries.

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 input schema covers 100% of parameters, so the baseline is 3. The description adds value beyond the schema by elaborating on the 'view' parameter's semantics (e.g., what 'settle' computes) and explaining the 'x_payment' flow. This goes beyond the schema's terse descriptions, particularly for the view enum and the payment 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 opens with a clear question that defines the tool's core purpose: 'Is a market open on a date, and why not if it isn't.' It then enumerates distinct views (next_session, settle, business_days, year), making it obvious this handles market calendars and settlement dates. This is differentiated from siblings like timezone and weather, which deal with time zones and weather rather than financial calendars.

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 provides explicit guidance for each view, telling the user exactly when to use 'next_session', 'settle', 'business_days', and 'year'. It also mentions the free `pricing` tool as an alternative for price-related needs, which helps avoid unnecessary paid calls. However, it does not explicitly contrast with other sibling tools, so the guidance is strong but not comprehensive.

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