company_funding

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

No annotations are provided, so the description must disclose behavioral traits. It describes the tool as researching external sources (Crunchbase, PitchBook, etc.), implying a read-only operation with no side effects. However, it does not explicitly state read-only behavior, auth requirements, rate limits, or what happens if the company is not found. The description is adequate for a simple research tool but lacks depth.

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 front-loaded with the main purpose in the first sentence, followed by specifics on data sources and a well-structured Args section. While slightly verbose (e.g., listing all sources), every sentence adds value. The length is appropriate for the complexity of the tool.

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 that an output schema exists (mentioned in context), the description does not need to detail return values. It covers the tool's scope (funding history, rounds, valuation, investors), parameter usage, and data sources. Missing elements like prerequisites (e.g., company existence) or limitations are not critical for a research tool. The description is sufficiently complete for an agent to use it effectively.

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 has 0% description coverage, so the description carries full burden for parameter semantics. The Args section explains all 5 parameters: company_name (required), output_format (with explicit options 'answer' and 'structured'), from_date and to_date (date ranges YYYY-MM-DD), and max_results (range 1-50). This adds significant meaning beyond the schema's titles and defaults.

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 it retrieves funding and valuation information, specifying the verb 'Get' and the resource 'funding and valuation information about a company'. It lists specific data types (funding history, rounds, valuation, investors) and sources (Crunchbase, PitchBook, etc.), distinguishing it from sibling tools like company_financials and company_overview, which cover broader or different aspects.

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 provide any guidance on when to use this tool versus alternatives, such as sibling tools like company_financials or company_overview. It lacks explicit 'when-to-use' or 'when-not-to-use' instructions, leaving the agent to infer context from the tool's name and sibling list.

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