Global Weather (MET Norway)

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

With no annotations, the description carries the full burden and does meaningful work: it discloses the cost model ('Paid per call via x402 (USDC on Base)') and data provenance (MET Norway global model, GeoNames 30k+ cities). It does not cover rate limits, caching, or error behavior, but the payment and sourcing disclosures are the material facts an agent needs before invoking.

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 verb and resource before the payload detail, then usage and payment. It is a single dense paragraph that is longer than strictly necessary (the full field enumeration could be trimmed) but every clause is informative rather than 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?

No output schema and six optional parameters, so the description must describe returns — and it does, listing current metrics, hourly outlook, and 7-day aggregates with precipitation totals and symbols. The payment flow is also explained (omit signature to receive payment requirements). Only the ambiguity of lat/lon vs. city precedence is left unresolved.

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 every parameter is already documented and the baseline is 3. The description adds only marginal semantics beyond the schema — worldwide validity of lat/lon and that city lookup is backed by GeoNames — but no precedence rule for city vs. lat/lon or country-filter interaction.

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?

Names the exact resource (weather), the accepted location inputs (city name or lat/lon), the specific return payload (current conditions, 24h hourly, 7-day min/max with precipitation), and the upstream model (Norwegian Meteorological Institute) plus GeoNames for city lookup. An agent knows precisely what this tool returns without opening the 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?

Explicitly states 'Use when an agent needs current conditions and a short-range forecast for any city or coordinate worldwide' and enumerates concrete scenarios (travel, logistics, events, field work). No exclusions or alternatives are given, but with no sibling tools there is nothing to route against.

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