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

No annotations are provided, so the description carries the full burden. It describes the tool as returning computed data (e.g., 'computed from the supply-chain graph'), implying a read operation, but does not explicitly state it is non-destructive, free of side effects, or whether authentication or rate limits apply. For a tool with no annotations, more explicit behavioral disclosure is needed.

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 a single paragraph of moderate length. It is front-loaded with the core purpose and lists specific data points, but could be more scannable with bullet points or shorter sentences. Every sentence adds information, but there is minor redundancy in the phrase 'inbound/outbound supplier-relationship edge counts' which is already implied by 'across this country's border'.

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 absence of an output schema, the description adequately explains what the tool returns (company count, segment breakdown, top companies, edge counts). It also clarifies a critical nuance: 'country is the company's HEADQUARTERS country only, not a manufacturing-footprint field', preventing misinterpretation. This completeness compensates for the lack of an output schema.

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 input schema already documents the single 'country' parameter with 100% coverage. The description adds value beyond the schema by noting case-insensitivity and recognition of common short forms (USA, UK, Korea), which helps the agent correctly format inputs.

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 provides a 'deep profile' of a country's presence in a specific semiconductor and AI supply-chain dataset, listing specific data elements (company count, segment breakdown, top companies, etc.). This is a specific verb+resource combination that distinguishes it from sibling tools like list_countries (simple list) or get_country_exposure (possibly narrower).

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 does not explicitly state when to use this tool versus alternatives (e.g., compare_countries or get_country_exposure). However, it implies use for a comprehensive single-country deep dive, and the sibling list provides context. No exclusions or conditions are mentioned, which is adequate but not exemplary.

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