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

Beyond the read-only/idempotent annotations, the description discloses important behavior: released items always have actual values, upcoming items never do, diff is a plain arithmetic difference with no consensus judgment, key_event is only an event-type flag, and sorting is major-economy-first. It also flags Yahoo's reporting lag and source-exposure caveats.

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 every sentence earns its place: purpose, source rationale, bucket invariants, filter semantics, sorting behavior, and tier restrictions are all covered without repetition. The front-loaded opening gives immediate clarity, and the structured sections make it easy to scan.

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 an output schema exists and all 5 parameters are documented in the schema, the description covers the remaining contextual ground fully: bucket semantics, value guarantees, filtering options, sorting behavior, reporting lag, and source caveats. Nothing an agent needs to safely invoke this tool is missing.

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%, so the baseline is a 3, but the description adds meaningful semantics beyond the schema: days defines the upcoming window, lookback_days defines the released window with a reporting-lag rationale, limit applies per bucket, and key_events_only/major_only map to described filtering behavior. This helps an agent use the parameters correctly in context.

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 states a specific verb ('get') and resource: upcoming and recently-released macroeconomic events, listing concrete event types like CPI, GDP, PMI, and payrolls. It clearly distinguishes itself from earnings-calendar and other financial-data siblings by focusing on macro/economic events.

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 makes the intended use explicit: retrieving macro/economic event calendars, with filters like key_events_only and major_only for narrower use cases. It also gives clear context about the data source and Pro-tier restriction, though it does not explicitly name when to use a sibling tool instead.

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