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

Annotations already declare the tool read-only, idempotent, open-world, and non-destructive. The description adds useful behavioral context by warning that omitting series_ids on a broad dataset returns every series it contains, which is valuable for managing response size. It does not describe output format or pagination, but the annotation coverage lowers the burden.

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, front-loaded with the tool's purpose, and uses a short second paragraph for guidance. Every sentence contributes meaningful information without repetition or filler.

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 rich input schema, presence of an output schema, and strong annotations, the description provides the necessary orientation and key caveat. It is sufficient for an agent to understand when to invoke this tool and how to avoid an overly broad result.

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?

All 11 parameters are described in the schema, so the baseline is 3. The description adds extra semantic value by explaining the practical effect of series_ids—narrowing a broad dataset instead of returning all series—which goes beyond the schema's 'keep after download' phrasing.

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 the tool as a source-aware convenience wrapper for returning the highest or lowest numeric observations. It also distinguishes itself from get_economic_series by noting when to prefer the alternative, satisfying the differentiation criterion.

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 explicitly instructs users to prefer get_economic_series for a single curated indicator and advises passing series_ids=[...] to avoid returning every series in a broad dataset. This provides clear when-to-use and when-not-to-use guidance beyond just stating purpose.

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