auroraLive Kp/aurora odds from Vigi-Sky (NOAA) plus France Kp 6/7/8–9 thresholds.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude WGS84 | |
| lng | No | Longitude WGS84. lon and lng are aliases — provide either. | |
| lon | No | Longitude WGS84. lon and lng are aliases — provide either. | |
| lang | No |
| Name | Required | Description | Default |
|---|---|---|---|
| aurora | No | ||
| citations | Yes | ||
| provenance | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / requiredAdded value: +[
+ "citations",
+ "provenance"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which align with the safe, read-only nature implied by 'Live Kp/aurora odds'. The description adds that it uses specific data sources and thresholds, which is helpful behavioral context but does not explicitly detail any additional behavioral traits beyond what annotations already cover.
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 a single, concise sentence that packs source, output type, and key details (thresholds) with no redundant words. It earns its place without any fluff.
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?
Given there is an output schema and annotations cover safety and idempotency, the description adequately completes the picture by specifying data source and France-specific thresholds. However, it could hint at the output shape (e.g., odds, KP index) to further aid an agent, though the output schema likely fills that gap.
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 75%, so the schema already documents three of four parameters fairly well (lat, lng, lon). The description does not elaborate on parameter meaning, leaving the schema to carry most of the burden. For the required 'lat' parameter, the description adds no extra semantics beyond what the schema provides. Baseline score of 3 is appropriate.
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 clearly identifies the tool as providing 'Live Kp/aurora odds' from a specific source (Vigi-Sky / NOAA) and includes mention of threshold values for France. It is distinct from siblings like 'solar' or 'first_skies', but does not explicitly differentiate itself from them.
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?
There is no guidance on when to use this tool versus other astronomy or observation tools. No alternatives or context-based suggestions are provided, leaving the agent to infer usage solely from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.