score_listing

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 describes the scoring computation and output components but does not state whether the operation is read-only, whether it has side effects, whether it requires special auth, or whether custom profiles affect computed results in any non-obvious way. The description does not contradict anything, but it leaves key behavioral traits unstated.

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 a single compact sentence that packs in the score range, the component breakdown, and the profile flexibility without filler. It is easy to read, though a more explicit verb or slight restructuring, such as 'Returns a project-car score...', would improve clarity. No unnecessary words are present.

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 presence of an output schema covers return-value details, and the schema already documents the profile parameter well. Still, with no annotations and no sibling differentiation, the description leaves an agent to infer that this is a read-only scoring action and when to choose it over analyze_listing. For a two-parameter tool this is adequate but not complete.

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 50%, with listing_id having no description. The description adds some value by clarifying that the profile can be 'named or custom', which complements the schema's detailed profile enum/object. However, listing_id semantics are still only implied by the tool name, and the description does not fully compensate for the missing schema description.

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 that the tool produces a 0-100 project-car score with per-component scores, weights, and explanations. It identifies the resource (a listing) and the profile dimension, so an agent can infer the core purpose. However, it lacks an explicit verb and does not distinguish this from sibling tools like analyze_listing.

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 gives no guidance on when to use this tool versus alternatives such as analyze_listing, analyze_market, or find_deals. It does not mention when a named profile is preferable to a custom profile, nor when the tool should not be used. Usage context must be inferred entirely from the tool name and schema.

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