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

Annotations already declare the non-read-only, open-world, non-idempotent, non-destructive profile, and the description adds real context beyond that: it is asynchronous (returns a job_id requiring polling) and it consumes credits, with a surcharge path. It also flags that urban_street_level only works for 53 US cities, a meaningful coverage limit not derivable from the 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?

Three sentences, zero filler, and the deliverable is front-loaded ahead of cost and workflow details. Even the parenthetical about hourly street-level air temperature from citizen stations adds decision-relevant substance rather than padding.

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, and the async job pattern, credit model, temporal scope, and urban-data limitation are all covered. The remaining gap is guidance on data_source and dc_edition choices, which an agent must guess for a tool with high side-effect cost.

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 0%, so the description carries the full burden, and it only explains two of eight parameters: the year window (1990 to last year) and urban_street_level (its cost and its 53-US-city restriction). lat, lon, api_key, dc_edition, data_source, and location_name remain entirely unexplained in both schema and description.

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?

"Start an actual-year (AMY) EPW + DDY + STAT for any point, 1990 to last year" gives a specific verb, three concrete output artifacts, and a scope. The AMY framing implicitly separates it from generate_tmy / generate_future_climate, though those siblings are never named.

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?

Supplies the practical context an agent needs before calling: credit cost (1, or +2 with urban_street_level) and the required next step, "poll with get_job_result". It stops short of stating when to prefer this over generate_tmy or generate_forecast, so it is clear context rather than full when/when-not guidance.

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