scout_company

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format (industry, funding, etc.), which is helpful, but lacks critical details like whether this is a read-only operation, requires authentication, has rate limits, or how it handles errors. For a tool that likely queries external data sources, this is a significant gap.

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 extremely concise and front-loaded, with two sentences that efficiently convey the core functionality and return values. Every word earns its place, and there's no redundant or verbose language.

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 tool's moderate complexity (2 parameters, no annotations), the description covers the basic purpose and return format adequately. Since an output schema exists, the description doesn't need to detail return values further. However, it lacks behavioral context (e.g., data sources, limitations), which slightly reduces completeness for a tool that likely involves external queries.

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 100%, so the schema already fully documents both parameters (name and domain). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or edge cases. The baseline score of 3 reflects adequate but minimal value added by the description.

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's purpose with a specific verb ('Get') and resource ('structured intelligence on any company'), making it immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'scout_person' or 'scout_product', which likely provide intelligence on different entity types rather than distinguishing within company intelligence.

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 no guidance on when to use this tool versus alternatives like 'scout_batch', 'scout_competitors', or 'scout_market'. It doesn't mention prerequisites, exclusions, or comparative use cases, leaving the agent to infer usage from tool names alone.

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