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by robobobby

no_current_weather

Retrieve current weather conditions for Norwegian locations using MET Norway data, including temperature, wind, precipitation, humidity, and cloud cover.

Instructions

Get current weather for a location in Norway using MET Norway (yr.no). Includes temperature, wind, precipitation, humidity, and cloud cover.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationYesNorwegian city name (e.g. 'Oslo', 'Bergen', 'Tromsø', 'Lofoten') or lat,lon coordinates

Implementation Reference

  • The 'no_current_weather' tool is registered and implemented within the server.tool block in src/servers/norwegian-weather.js. It fetches weather data from the MET Norway API and formats it into a text response.
    server.tool(
      "no_current_weather",
      "Get current weather for a location in Norway using MET Norway (yr.no). Includes temperature, wind, precipitation, humidity, and cloud cover.",
      {
        location: z.string().describe("Norwegian city name (e.g. 'Oslo', 'Bergen', 'Tromsø', 'Lofoten') or lat,lon coordinates"),
      },
      async ({ location }) => {
        try {
          const loc = await getLocation(location);
          const data = await fetchForecast(loc.lat, loc.lon);
          const ts = data.properties.timeseries;
          if (!ts?.length) throw new Error("No forecast data available");
    
          const now = ts[0];
          const inst = now.data.instant.details;
          const symbol = now.data.next_1_hours?.summary?.symbol_code
            || now.data.next_6_hours?.summary?.symbol_code || "";
          const precip1h = now.data.next_1_hours?.details?.precipitation_amount;
    
          const lines = [
            `## ${loc.name} — Current Weather`,
            `**Conditions:** ${symbolToText(symbol)}`,
            `**Temperature:** ${inst.air_temperature}°C`,
            `**Humidity:** ${inst.relative_humidity}%`,
            `**Wind:** ${inst.wind_speed} m/s from ${inst.wind_from_direction}° (gusts ${inst.wind_speed_of_gust ?? "N/A"} m/s)`,
            `**Pressure:** ${inst.air_pressure_at_sea_level} hPa`,
            `**Cloud cover:** ${inst.cloud_area_fraction}%`,
            precip1h != null ? `**Precipitation (next hour):** ${precip1h} mm` : null,
            `\n*MET Norway Locationforecast 2.0 — ${now.time}*`,
          ].filter(Boolean);
    
          return { content: [{ type: "text", text: lines.join("\n") }] };
        } catch (err) {
          return { content: [{ type: "text", text: `Error: ${err.message}` }], isError: true };
        }
      }
    );
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It lists included weather metrics (temperature, wind, precipitation, humidity, cloud cover) but doesn't cover critical aspects like rate limits, authentication needs, error handling, data freshness, or response format. For a tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise and front-loaded, with the core purpose stated first followed by details on included metrics. Both sentences earn their place by clarifying scope and data elements. It avoids redundancy and waste, though it could be slightly more structured (e.g., separating usage context from data details).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for effective tool use. It covers what data is included but omits behavioral traits (e.g., rate limits, errors), response structure, and usage guidelines relative to siblings. For a tool with no structured support, the description should provide more comprehensive context to compensate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'location' parameter clearly documented in the schema itself. The description adds no additional parameter semantics beyond what's in the schema (e.g., no examples of valid location formats beyond those implied). Since the schema does the heavy lifting, the baseline score of 3 is appropriate, though the description doesn't compensate or enhance parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get current weather for a location in Norway using MET Norway (yr.no).' It specifies the action ('Get'), resource ('current weather'), and geographic scope ('Norway'), distinguishing it from sibling tools like 'dk_current_weather' or 'se_current_weather'. However, it doesn't explicitly differentiate from 'no_weather_forecast', which is a minor gap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions the data source ('MET Norway (yr.no)') but doesn't specify when to choose it over sibling tools like 'no_weather_forecast' or other country-specific weather tools. There's no mention of prerequisites, exclusions, or comparative contexts.

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

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