Price Stats

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower. The description still adds real value by disclosing that this is 999.md's own estimate rather than a computed figure, and warns that min/max/average are skewed by mistyped prices — a behavioral caveat not present in any structured field.

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?

Two tight sentences, the output contents stated first and the median-preference caveat second. Every sentence earns its place with no 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?

An output schema exists, so return values need not be described. The description is complete enough for a read-only stats tool, though it omits any pointer to how options map to get_filters and gives no usage context against siblings.

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 67% and the schema itself explains category, options (with get_filters/filter narrowing) and currency. The description adds no parameter-level meaning, so it neither compensates for the coverage gap nor extends 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?

States a specific verb+resource ('999.md's own price estimate over matching ads') and enumerates exactly what is returned: median, average, min, max and sample size. An agent can immediately tell this is a statistical aggregation tool, distinct from siblings like search or get_ad which return individual listings.

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 offers analytical guidance ('Prefer the median') but no operational when-to-use guidance: it never says when to call price_stats instead of search, or what prerequisites (e.g. category/options) are needed. The one alternative it hints at is a statistical measure, not a sibling tool.

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