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

With no annotations, the description fully discloses the dataset scope (29 countries, 615 companies), the output contents (counts, segment presence, public/private split, market-cap totals), the sort order, and the crucial distinction between HQ country and manufacturing footprint. This goes well beyond basic tool purpose.

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 packed with useful details: dataset scope, output fields, sorting, optional filter, and a critical data interpretation warning. Each sentence contributes essential information without redundancy.

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?

The description covers the essential output contents, the dataset size, sort order, and a major caveat about HQ vs production geography. For a one-optional-param listing tool with no output schema, this is comprehensive. The only minor gap is whether the segment filter affects the country list or just counts, but the schema's 'Restrict to companies' clarifies it filters the underlying set.

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 schema already documents the only parameter 'segment' with details on case-insensitivity and examples. The description merely repeats it as 'Optional segment filter' without adding new information. Baseline 3 applies due to 100% schema coverage.

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 lists all countries in the dataset with company counts, segment presence counts, public/private split, and market-cap totals. It distinguishes from sibling tools like get_country_profile or compare_countries by emphasizing it covers every country and is sorted by count.

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 clear usage context: this is an overview listing sorted by company count, with an optional segment filter. It also includes an important caveat about HQ country semantics, which guides proper interpretation. However, it does not explicitly name alternative tools for single-country or comparison use cases.

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