lookup_company

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

With no annotations, the description carries the full behavioral burden. It discloses two useful traits: only the 'best match' is returned (not all matches), and parent companies are only included optionally. It omits auth requirements, rate limits, and whether matching is exact or fuzzy — meaningful gaps for a no-annotation tool.

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?

Three sentences, no filler: what it does, the optional argument and its benefit, and what comes back. The purpose is front-loaded and the value of the country code is stated inline rather than buried.

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 low-complexity read-only lookup with an output schema present, the description need not describe return shapes, and it still summarizes them. The remaining gap is edge behavior — no-match handling and match-exactness — which an agent would need in practice.

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 0%, so the description must compensate, and it largely does: 'name' means legal name, 'country' is spelled out as ISO 3166-1 alpha-2 with concrete examples and a stated payoff ('much better match'), and '(optionally) parent companies' maps to include_parents. It never names include_parents directly, leaving that binding slightly implicit.

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?

States a specific verb and resource ('Find a company') plus the backing dataset ('GLEIF open data'), and the qualifier 'by legal name' implicitly separates it from lookup_lei (identifier-based) and bulk_lookup. It stops short of naming the siblings explicitly, so an agent must infer the boundary rather than read it.

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 clearly frames the use case (lookup by name) and advises passing a country code for a 'much better match', which is a real usage hint. However, it never says when to prefer lookup_lei or bulk_lookup, nor addresses name ambiguity or what to do if no match is found.

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