Company Insights

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the sync/async execution modes and the return style for each ('direct response payload' vs 'async request metadata'), and mentions tracking with requests_get. It does not delve into rate limits, authentication, or error conditions, but for a read-only enrichment tool this is a reasonable level of detail.

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 well-organized into clear sections with headers, making it easy to scan. It is front-loaded with the core purpose and maintains focus, though there is some redundancy between the 'Best for' and 'Prefer this tool when' sections that could be trimmed without losing meaning.

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 tool's primary purpose, typical use cases, alternative tools, and both sync and async execution behavior. Since an output schema is present, the absence of a detailed return-field breakdown is acceptable. It lacks explicit discussion of webhook behavior and error handling, but overall it is complete enough for an agent to select and invoke the tool correctly in most situations.

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 all six parameters with 100% coverage, including descriptions for query, fields, webhook, enrichments, and execution_mode. The description adds contextual guidance on when to use async versus sync mode, but does not meaningfully enhance parameter-level semantics beyond what the schema provides, so the baseline 3 is appropriate.

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 opens with 'Get structured company-level insight data from Outscraper,' identifying a specific verb, resource, and data type. It further clarifies the scope with concrete examples (firmographics, size, revenue, industry, founding) and explicitly distinguishes itself from the sibling tool emails_and_contacts.

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 explicit 'Prefer this tool when' and 'Use emails_and_contacts instead when' sections, clearly defining when to use this tool versus a direct alternative. It also gives guidance on choosing async mode for large batches and expensive enrichment, leaving no ambiguity.

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