Retrieves solar X-ray flares, active alerts, and auroral oval data to diagnose GPS and HF signal degradation.
SWPC space weather — solar X-ray flares, active alerts, and the auroral oval. The causal layer under GPS/HF degradation.
| Name | Required | Description | Default |
|---|---|---|---|
| detail | No | short |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden and largely drops it. It conveys that this is observational space-weather data, but says nothing about freshness or cadence (live vs. archive), coverage, or whether alerts are pre-filtered — all material for a monitoring feed. Output schema existence covers return shape but not behavior.
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?
Two short sentences, dataset enumeration front-loaded, no filler or repetition. The second sentence is evocative rather than operational, which slightly reduces its utility but it is still compact.
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?
The output schema relieves the description of explaining return values, and the enumerated datasets give a reasonable sense of content. However, for a monitoring feed with one undocumented parameter and no annotations, the definition leaves out verbosity control, data freshness, and geographic scope — enough gaps that an agent would be guessing on invocation details.
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 0% for the single 'detail' parameter, which has a default of 'short' and no enum defined. The description never mentions 'detail' or what values it takes, so the agent gets no help on how to control verbosity. A one-param tool with zero coverage needs the description to compensate, and it does not.
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 names a concrete source (SWPC) and enumerates the specific datasets returned: solar X-ray flares, active alerts, and the auroral oval. That is more than a restated name. It does not explicitly differentiate itself from nearby siblings such as gps_jamming, radiation, or aviation_sigmet, though the 'causal layer' phrasing hints at the relationship.
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 causal layer under GPS/HF degradation' implies when the tool is useful — correlating with GPS jamming or HF/aviation signal problems — but never states it directly. No alternative tool is named, no when-not condition is given, and nothing tells the agent whether to reach for this or gps_jamming/radiation first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.