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

Annotations already declare a safe read (readOnlyHint true, openWorldHint false). The description adds real context: reliance on 30-day history and, notably, that fields are null during data gaps — a behavioral trait not in annotations or schema.

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?

One dense sentence front-loads the verdict then qualifies scope and the 30-day basis; the null-fields caveat is tacked on but earns its place. Slightly compressed but not bloated.

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 no output schema, the description covers the core judgment plus a key edge-case (null fields during gaps) and the trend basis. It does not describe the shape/fields of the verdict itself, a modest gap for a computed-judgment tool.

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 100% and the single parameter already documents its source (list_cities/search_locations). The description adds no further parameter detail, so the schema baseline of 3 applies.

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 purpose: a fair-price assessment and fill-now-or-wait verdict for a Quebec city, distinct from siblings like get_city_prices or find_cheapest_stations which list prices vs. render a judgment.

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 decision framing for waiting vs. filling is clear, but no explicit guidance on when to prefer this over get_city_prices or find_cheapest_stations, nor prerequisites beyond an implied city_slug lookup.

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