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

With no annotations, the description carries full burden and does so thoroughly. It discloses that data are estimates, includes per-row confidence, describes return structure (regions, countries, concentration metrics), and warns about currency code absence and period-to-period currency changes. It also clarifies that each layer sums to 100, preventing misuse.

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 long but information-dense, with no wasted words. It front-loads the core purpose and then covers caveats. It could be better formatted with bullets, but every sentence adds value, so it earns a 4.

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?

For a tool with no output schema and no annotations, this description is exceptional. It covers the return fields (regions, countries, concentration metrics, period), explains the country-filter history behavior, gives interpretation guidance (percent vs amount), and points to an alternative. It fully equips an agent to invoke and interpret the tool.

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 only 17%, so the description must compensate. It adds meaning for the country parameter (comma-separated codes, per-period history), implies layer controls hierarchy, and mentions period. However, it does not explain top_countries or company_id, nor does it define layer value meanings, leaving some parameters ambiguous.

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's purpose: it estimates geographic revenue exposure for a single company by region/country with confidence scores. It distinguishes itself from sibling tools by emphasizing the tariff/geopolitical lens and explicitly contrasts with reported segments via /fundamentals/segments/{ticker}.

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 strong usage guidance: it says to use this for names that never break out geographic revenue, and explicitly says to use /fundamentals/segments/{ticker} instead for reported segments. This gives an explicit alternative and clear when/not-to-use context.

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