Estimate a price from comparables

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

Beyond the annotations (readOnlyHint=true, openWorldHint=true), the description discloses critical behaviors: the tool may run a search itself (openWorldHint), it removes outliers, it outputs active asking prices (not sale prices) due to Leboncoin's lack of transaction data, and it deliberately provides no recommended price at `insufficient_data`. These details add significant transparency beyond the structured annotations and directly impact agent behavior.

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 relatively detailed but appropriately so, given the tool's complexity (25 parameters, no output schema). It front-loads the primary purpose and output summary, then adds important usage caveats. The bolded **Respect `confidenceLabel`** draws attention to a critical instruction. No redundant content, though it could be slightly more compact.

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?

Since there is no output schema, the description thoroughly covers the return values (statistics, outliers, recommendation, confidence score). It also explains the confidenceLabel semantics, the handling of insufficient data, and the nature of the prices (asking vs. sale). Combined with high parameter schema coverage, the description leaves little ambiguity for an agent to use the tool correctly.

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 84% (high), so the baseline is 3. The description adds meaning by explaining the two distinct input modes (using `comparables` vs. providing item facts) and clarifies that the tool can operate in either mode. While it does not elaborate on each parameter, it contextualizes the overall input strategy, which goes beyond what the schema alone provides.

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 function: 'Turns comparable ads into a price distribution and a recommendation' and enumerates the specific outputs (min, Q1, median, etc.). It also distinguishes itself from sibling tools by describing two invocation modes (pass comparables or run search) and mentioning the confidenceLabel behavior, which is not present in other pricing-related siblings like analyze_market_price.

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 explicit usage instructions: either pass `comparables` from a previous search, or pass item facts to let the tool run its own search. It also advises on how to handle `insufficient_data` (communicate lack of data, do not quote a number) and cautions against phrasing results as sale prices. However, it does not explicitly state when to choose this tool over alternatives like `analyze_market_price`, though the distinct scope is implied.

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