data_sourcesReveals data origins and caveats for the air quality readings. Use it to verify source reliability and understand limitations before interpreting station or forecast data.
Where the data comes from and caveats.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds essentially no behavioral context beyond that — it doesn't say whether this returns provenance metadata, a list, external references, or how large/stable the result is.
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?
It is short with no wasted words, but it is a sentence fragment that is not front-loaded with a verb and reads as a caption rather than a definition. Brevity here reflects under-specification more than discipline.
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?
With no output schema and no parameters, the description is the only source of information about what this tool yields, and it does not explain the return content, structure, or the nature of the 'caveats'. For a metadata/provenance tool it leaves the agent guessing.
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 tool takes zero parameters, so the baseline of 4 applies; there is no parameter semantics for the description to clarify.
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 is a noun-phrase fragment ('Where the data comes from and caveats') that essentially restates the name and title. There is no verb and no statement of what the tool actually returns or does, so an agent cannot confidently distinguish it from siblings like air_quality or air_stations.
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?
Nothing indicates when to call this rather than air_quality or air_stations, nor any prerequisite or exclusion. Usage is at best implied by the word 'caveats', which is too weak to count as guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.