get_ai_tool_prices

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

With no annotations provided, the description carries the full burden. It explains the data source, verification status, and output fields, but omits details about pagination, error handling, rate limits, or authentication. The behavior is somewhat transparent but not fully comprehensive.

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 fairly concise and well-structured, starting with the tool's purpose, then output, source, and filtering options. It could be slightly more compact but is efficient and easy to parse.

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 has no output schema, the description compensates by listing the returned fields. It includes source info and valid categories, and covers the four optional parameters. Missing details like pagination or error behavior are minor given the tool's straightforward nature.

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 baseline is 3. The description adds value by providing the list of valid categories and explaining that 'query' can match against name, description, id, or category. This goes beyond the schema descriptions.

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: retrieving current, human-verified pricing for over 100 AI tools used by solo builders. It lists specific categories and output fields, distinguishing it from the sibling tool 'calculate_ai_margin' which is about margin calculation.

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 explains the tool's capabilities and filtering options (by category, query, or exact id), but does not explicitly mention when not to use it or compare it directly with the sibling tool. However, the context is clear enough for an agent to decide.

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