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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds behavioral context by noting it is a 'convenience wrapper' and that without series_ids it returns every series in the dataset, which is useful beyond the annotations. No contradictions with annotations.

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 two sentences long, front-loaded with the core purpose and followed by targeted usage guidance. Every sentence earns its place, and there is no repetition of schema or annotation content.

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 an output schema and rich annotations, the description need not explain return values or safety. It covers the key alternative (get_economic_series) and the series_ids narrowing behavior, which are the most important decisions for an agent. It is slightly sparse on distinctions from other siblings like get_top_observations, but adequate given the schema coverage.

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 provides 100% parameter description coverage, so the baseline is 3. The description goes further by explaining the semantic role of series_ids—narrowing a broad dataset instead of returning every series—and by advising get_economic_series for single-indicator concepts. This adds value beyond the structured schema.

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 this as a 'source-aware convenience wrapper' for retrieving the latest observations, with the name and title reinforcing the purpose. It also distinguishes itself by recommending get_economic_series for single curated indicators. However, it relies on the metaphorical 'wrapper' phrasing rather than a direct verb+resource statement.

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 explicitly tells the agent to prefer get_economic_series(concept=...) for a single curated indicator and advises passing series_ids=[...] to narrow a broad dataset instead of returning every series. This provides a clear when-not and alternative while implying the tool's own use case for broad, source-aware latest observations.

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