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

Annotations already mark it read-only and open-world, but the description adds meaningful operational context: exact price ($0.002 per successful call), payment networks (Base, Solana, Arc), and the important distinction that failed calls are not charged. It also summarizes the returned fields, reducing uncertainty about response contents.

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 core search purpose and filters, followed by return fields and pricing. It is dense but mostly earns its length; the long return-field list duplicates the output schema somewhat, which keeps it from being maximally concise.

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 eight optional parameters, an output schema, and read-only/open-world annotations, the definition supplies what the agent needs: dataset scope, filter dimensions, returned fields, match count, and pricing behavior. Remaining details such as pagination defaults are fully covered by the 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?

Schema description coverage is 100%, so all eight parameters are already documented in structured form. The description restates the filters at a high level but adds no syntax, edge-case, or interaction detail beyond the schema.

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 states a specific verb-and-resource pair: searching and filtering Techstars portfolio companies, with the dataset size (5,600+) and exact filter dimensions. The resource is clearly distinct from sibling directories such as b2b_y_combinator, so an agent can identify what this tool covers without opening the schema.

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?

It explains the searchable fields and filters, which implies when the tool is useful, but it does not say when to choose it over alternatives or when not to use it. No sibling tool is named as a comparison point.

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