Price History

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

Annotations already declare readOnly/idempotent/closed-world, so the description's job is content disclosure and it does that well: it reveals that results mix observed changes with probabilistic 90-day and 1-year forecasts for unchanged listings, which is behavior an agent could not infer from the schema. It does not mention pagination or result limits, but the read-only profile is already covered.

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?

It is one dense sentence but front-loads the primary payload (changes since 2023) before the forecast clause and the date clause. No filler or marketing language, though the sentence is long enough that the '90 days and year' forecast clause reads as a run-on.

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 an output schema present, the description needn't enumerate return fields, and it still conveys the two modes (history vs. dated snapshot) plus the forecast component. The main omission is guidance on choosing this tool versus siblings, which is a usage gap rather than a completeness-of-behavior gap.

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 100%, so the schema already documents both parameters, including the YYYY-MM-DD format for date and the listing-name form for model. The description only restates the date behavior ('each listing's prices that day') without adding format or edge-case meaning beyond the schema. Baseline 3 is appropriate.

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 states a specific resource (a model's listing changes since 2023 plus forward-looking change/retirement probabilities) and what a date adds, so the agent knows this is a historical-plus-forecast lookup rather than a search or cost tool. It never names a sibling to contrast against, so differentiation from find_models or not_yet_priced is left to inference.

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?

There is no explicit when-to-use statement or condition selecting this tool over alternatives. The only conditional phrasing ('With a date...') explains the effect of a parameter, not when an agent should reach for this tool versus its nine siblings.

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