Get Top Observations

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, lowering the burden. The description adds useful behavioral context: it is a 'convenience wrapper' and warns that without narrowing, it may return every series in the dataset. No contradictions with annotations. Slightly more detail could be provided about return shape, but overall good.

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 compact and front-loaded: the first sentence states purpose, and the second provides usage alternatives. No redundant phrases; every sentence contributes. It is well-structured and appropriately sized for the tool's complexity.

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 has 11 parameters and an output schema, the schema handles details. The description provides the essential conceptual context (wrapper, highest/lowest, source-aware) and high-level usage guidance. It could explicitly note that it aggregates across sources, but the schema's source enum already covers that. Overall complete enough for an agent to select and invoke correctly.

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 references series_ids for narrowing, but parameter semantics are mostly handled by the schema's detailed per-parameter descriptions. The description adds marginal value beyond the schema, so a 3 is appropriate.

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 states the tool's purpose: a 'source-aware convenience wrapper for highest or lowest numeric observations.' It uses a specific verb ('get'), resource ('top observations'), and explicitly differentiates from siblings by mentioning prefer get_economic_series for single indicators. This is a clear and distinguishing purpose.

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 explicit guidance: use this tool for highest/lowest observations, but prefer get_economic_series(concept=...) for single curated indicators. It also advises passing series_ids=[...] to narrow a broad dataset. This clearly states when to use and when to use alternatives, exceeding basic guidance.

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