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Air Quality

get_air_quality
Read-onlyIdempotent

Returns current air quality index (AQI) and pollutant readings for Sedona, AZ from Open-Meteo. Includes US AQI category, PM2.5, PM10, ozone, and UV index. Especially useful during wildfire season for tracking smoke and outdoor safety.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes
us_aqiYes
updatedYes
categoryYes
locationYes
uv_indexYes
dust_ug_m3Yes
pm10_ug_m3Yes
coordinatesYes
ozone_ug_m3Yes
pm2_5_ug_m3Yes
carbon_monoxideYes
nitrogen_dioxideYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "carbon_monoxide": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "category": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "coordinates": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "lat": {
      +          "type": "number"
      +        },
      +        "lon": {
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "lat",
      +        "lon"
      +      ],
      +      "type": "object"
      +    },
      +    "dust_ug_m3": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "location": {
      +      "type": "string"
      +    },
      +    "nitrogen_dioxide": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "ozone_ug_m3": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "pm10_ug_m3": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "pm2_5_ug_m3": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "source": {
      +      "type": "string"
      +    },
      +    "updated": {
      +      "type": [
      +        "string",
      +        "null"
      +      ]
      +    },
      +    "us_aqi": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    },
      +    "uv_index": {
      +      "type": [
      +        "number",
      +        "null"
      +      ]
      +    }
      +  },
      +  "required": [
      +    "location",
      +    "coordinates",
      +    "updated",
      +    "us_aqi",
      +    "category",
      +    "pm2_5_ug_m3",
      +    "pm10_ug_m3",
      +    "ozone_ug_m3",
      +    "uv_index",
      +    "dust_ug_m3",
      +    "carbon_monoxide",
      +    "nitrogen_dioxide",
      +    "source"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds context about the data source (Open-Meteo) and location (Sedona, AZ), which is useful beyond annotations. No contradictions.

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

Conciseness5/5

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

The description is two concise sentences. The first sentence states the core purpose and data items; the second adds a practical use case. Every sentence is informative with no wasted words.

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

Completeness5/5

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

With zero parameters and an output schema present, the description is sufficient. It lists the specific data items returned, which adds value beyond the schema. No gaps in context.

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

Parameters4/5

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

The tool has zero parameters, so the input schema is empty. The description does not need to add parameter info; a baseline of 4 is appropriate.

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

Purpose5/5

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

The description clearly states it returns current air quality index and pollutant readings for Sedona, AZ. It lists specific data points (US AQI category, PM2.5, PM10, ozone, UV index) and the source (Open-Meteo), making the purpose unambiguous and specific.

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

Usage Guidelines4/5

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

The description includes a use case: 'Especially useful during wildfire season for tracking smoke and outdoor safety.' This provides context for when to use the tool, though it does not explicitly state when not to use or mention alternatives.

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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