Used-car market price stats

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

The annotations already declare readOnly/idempotent/non-destructive, but the description adds genuinely new behavior: it samples only the first pages of the newest-updated matching ads, keeps only fixed-price listings (excluding negotiable, installment and presale), and reports in Toman. It also discloses the key limitation that this is a sample of asking prices, not a census nor sale prices — a caveat an agent would otherwise misread as ground truth.

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?

Front-loaded with the output shape, then the use case, then the sampling caveat, then the follow-up routing — a sensible order with little filler. Slightly dense but every sentence contributes a distinct fact.

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?

With 9 optional parameters and no output schema, the description does the needed work by sketching what comes back (per-year price stats in Toman) and how the sample is built. It leaves minor gaps such as behavior when no ads match or how many samples back the stats, but nothing that would cause a mis-call.

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 78%, so the schema already carries most parameter meaning, including the vehicle path format and the mileage=0 convention. The description only gestures at narrowing via 'year, mileage and region', adding no semantics for seller, transmission, pages, or year bounds beyond what the schema states, so it sits at the baseline.

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: price statistics (min, quartiles, median, max, per year) for a car model drawn from live Bama ads. It immediately distinguishes itself from ba_search by describing that sibling as the place to see the actual ads, so an agent can choose between stats and listings without opening a schema.

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?

'Use it for "what is a 1398 Peugeot 206 worth" questions' gives a concrete triggering question shape, and the closing sentence prescribes a workflow: narrow with year/mileage/region for a tighter range, then switch to ba_search with sort=cheapest to inspect real ads. That names both the condition and the alternative tool.

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