suggest_price

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

With no annotations, the description does real work: it discloses the statistical method (median), outlier handling (IQR), rounding, and that representative `examples` come back and should be surfaced to the user. It omits failure behaviour — e.g. what happens when too few comparables exist — which matters for a price estimate.

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?

Short and front-loaded: method first, then default-usage rule, then parameter naming guidance, then output handling. The line break layout is slightly noisy but every sentence adds information.

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?

An output schema exists, so return values need no explanation, and the description still usefully flags `examples` as a field to show. The main gap is the undocumented `condition` parameter and unstated behaviour when no comparable ads are found.

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 coverage is 0%, so the description must carry all parameter meaning. It compensates well for `query` by defining it as short brand+model search words with a concrete example, but `condition` (the 1-5 enum) is never mentioned, leaving half the parameters undocumented.

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?

States a specific verb+resource with its exact derivation method ("median of comparable 'Til salgs' ads on finn.no Torget"), which no sibling tool offers. It is clearly distinguishable from suggest_category and the search tools.

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?

"Default price source whenever the user did not name a price" gives an explicit selection rule an agent can act on. It stops short of naming an alternative tool or stating when not to call it (e.g. category mismatch), so it is not full when/when-not coverage.

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