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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context: the data provenance (statistics offices, central banks, OECD, FRED), the returned shape (latest print with period, change, source, optional history), and what happens with empty arguments. Auth and rate-limit behavior are unspecified but low-risk for a read-only catalog tool.

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?

Purpose and scope lead, followed by return shape and the default/catalog behavior; the structure is front-loaded and the closing sentences are tight. The long mid-sentence domain enumeration is dense but it is the substantive content that justifies the tool's breadth, so it earns its space.

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?

With 7 optional parameters, 100% schema coverage, and no output schema, the description supplies what the schema cannot: the content of the returned readings and the empty-argument default. It does not state the history-size implications of combining history with since, nor any truncation behavior, but nothing critical for a correct first call 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 3. The description goes beyond the schema by explaining the interaction between parameters — that omitting keys and terms yields headline readings, and that catalog: true enumerates all keys — which clarifies the default-resolution order an agent would otherwise have to guess.

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 names a specific resource (economic indicators) with explicit geographic scope (US, EA, UK, JP) and enumerates the covered domains (inflation, growth, labour market, housing, public finances, etc.), which effectively separates it from narrow siblings like get_policy_rates or get_yield_curves. It stops short of explicitly naming which sibling to use for overlapping content, but the breadth is unambiguous.

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 gives a useful invocation pattern — "Without keys or terms it returns the headline readings; catalog: true lists every key" — which tells an agent how to bootstrap discovery. However, it never states when to prefer this tool over siblings such as get_policy_rates or search_macro_views, so sibling selection is left to inference.

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