get_market_liquidity

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

With no annotations, the description carries the full burden. It discloses the cost of 6 credits per call and the auto-refund policy, adding context beyond the basic purpose. The term 'estimated' signals that the result is an approximation, further enhancing transparency about the nature of the output.

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 exceptionally concise, with only two sentences. The core purpose is front-loaded, and the cost/refund information is efficiently stated without any redundancy.

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?

For a simple read-only tool with an output schema, the description is largely complete: it explains what the tool does, includes cost and failure handling, and the parameters are self-explanatory. However, the lack of usage guidance relative to sibling tools prevents a perfect score.

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 schema description coverage is 0%, so the description must compensate by explaining the parameters. It does not mention make, model, or year at all, leaving the agent to rely solely on the parameter names. This is a significant gap since the description provides no additional meaning 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 clearly states the tool returns estimated days-on-market (DOM) for a car in Poland, using a specific verb and resource. This distinguishes it from sibling tools like get_price_history and get_market_valuation, which deal with price and valuation rather than liquidity.

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 implies the use case—when you need to know how fast a car sells in Poland—but does not explicitly state when to use this tool over alternatives. It also omits any exclusions or prerequisite conditions, leaving the agent to infer the appropriate context from the tool's purpose.

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