get_economic_calendar

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

With no annotations, the description carries the full burden. It discloses that sources are live, free, and keyless, that each row shows actual or previous readings, and includes a critical caveat about the 'prior' label. This goes beyond a simple 'returns calendar events' statement and helps the agent set correct expectations about data semantics.

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 well-structured into three focused paragraphs: purpose, sources, and data interpretation caveats. Each sentence adds unique value, avoiding redundancy. The length is justified by the tool's complexity, and the most important info 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 tool's moderate complexity, the description covers the essential behavioral aspects: sources, available event types, actual vs previous readings, and the lack of forecasts. The output schema likely handles return field details, so the description need not duplicate that. Minor omissions like timezone or response size are acceptable but keep it from a 5.

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 100%, so the baseline is 3. The description reinforces the 'sources' parameter by naming BLS, Fed, and BEA, but does not add new meaning for days_back, days_ahead, or include_latest_data beyond what the schema already provides. Thus it meets, but does not exceed, the baseline.

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 identifies the tool's function: listing upcoming US macroeconomic events with scheduled dates/times and actual or previous values. It specifies the data sources (BLS, Fed, BEA) and event types (CPI, PPI, NFP, FOMC, PCE), distinguishing it from generic calendar or market tools.

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 clear context on when to use the tool (for US macro releases) and explicitly states exclusions: it has no consensus/expectations feed, and prior figures should not be read as forecasts. While it doesn't name alternative tools, the guidance on limitations is strong and actionable for an agent deciding to invoke it.

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