ImotAI rough value positioning

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

With no annotations, the description carries the full burden and does so well: it discloses the data source, the return shape (estimate, low-high range, confidence from sample size, disclaimer), a refusal threshold, and two hard behavioral obligations (verbatim disclaimer display, never call it an official valuation).

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?

Four sentences, each load-bearing: scope and data basis first, then return shape, then the refusal rule, then the compliance constraints. No redundancy or filler.

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?

No output schema exists, and the description compensates by enumerating the returned fields and the confidence derivation. The refusal condition and disclaimer obligations round out everything an agent needs to call and report this 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 coverage is already 80%, so the schema documents city/district/propertyType/area on its own. The description restates the filter dimensions but adds no format or syntax detail, and says nothing about the accepted-but-unused 'rooms' parameter, which the schema itself flags.

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 ('rough price positioning for a property') plus the filtering dimensions and, crucially, the data basis (current asking prices of active listings, not closed transactions). This distinguishes it immediately from get_property and get_market_stats.

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?

Gives clear conditions: usable only with at least 5 comparables, and grounded in asking rather than closed prices. It doesn't explicitly name sibling alternatives to use instead, but the scope statement effectively tells the agent when this tool is and isn't the right call.

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