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

No annotations exist, so the description carries full burden. It does disclose the returned fields (time in UTC, currency, impact, forecast, previous), which is genuinely useful context, but says nothing about the 7-day default window behavior, data freshness, ordering, or result limits.

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?

Two dense sentences with no filler; contents and returned fields come first, filters second. Every clause earns its place.

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?

An output schema exists, so the description needn't formalize return structure, and it supplies enough about contents and filters to call confidently. The only real gap is the meaning and effect of the `days` parameter.

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?

With 0% schema description coverage, the description must compensate. It defines the impact filter's allowed values (High, Medium, Low) and explains the currency filter, but leaves the `days` parameter entirely unexplained beyond the implicit 'this week' framing, so one of three parameters is undocumented.

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?

States a specific resource (this week's macroeconomic calendar) and enumerates concrete contents (CPI, jobs, GDP, PMIs, central-bank decisions) plus returned fields. No sibling is named, but the scope is unambiguous against the many market-data siblings such as central_bank_rates or fred_series.

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?

It mentions filtering by impact and currency, which implies how to narrow results, but never states when to prefer this over central_bank_rates, fred_series, or us_treasury_yields, nor any exclusions. Usage is only inferable from the described contents.

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