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 paid cost flow ($0.0011 inbound and proxied), the upstream URL, the HTTP method (GET), the data provider (Open-Meteo), and the returned data categories. It does not mention rate limits or error behavior, but for a read-only weather proxy the key behavioral context is present.

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?

The description is compact and front-loaded with the cost indicator, then states what the tool does, its inputs, outputs, and upstream details. The embedded example query is slightly dense but earns its place because the schema lacks specific parameter definitions.

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?

Despite having no output schema and no annotations, the description covers the essential invocation details: cost, query parameters, upstream URL, HTTP method, and returned fields. It lacks explicit routing guidance among the many sibling weather tools, but an agent has enough context to call this tool correctly.

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?

The schema only defines generic body and query containers, so the example query in the description is essential. It names the actual parameters (lat, lon, location), gives example values, explains that location is an alternative to lat/lon, and notes that lat must be used with lon. This goes well beyond the schema and is critical for correct invocation.

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 clear, specific purpose: real-time weather data and a 3-day forecast for any location, with explicit input options (city name or lat/lon) and output fields (temperature, humidity, wind, precipitation, conditions). This differentiates it from narrower weather siblings by emphasizing worldwide coverage and the forecast window.

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 implies usage context: use when needing weather for any location, or for a 3-day forecast, and accept either city name or coordinates. However, it does not explicitly state when to prefer this tool over the many sibling weather tools, nor does it mention exclusions or alternatives.

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