Vigi-Sky

Solar

solar

Read-onlyIdempotent

Live solar/CME context plus current Kp from Vigi-Sky APIs.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description	Default
`cme`	No
`aurora_kp`	No
`citations`	Yes
`provenance`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed5 schema fields changedAug 18, 2026
- addedOutput schema / properties / aurora_kp
```
Added value: +{
+  "type": "object"
+}
```
- addedOutput schema / properties / cme
```
Added value: +{
+  "type": "object"
+}
```
- removedOutput schema / properties / doctrine
```
Removed value: -{
-  "type": "string"
-}
```
- addedOutput schema / properties / provenance / properties / never
```
Added value: +{
+  "type": "string"
+}
```
- addedOutput schema / required
```
Added value: +[
+  "citations",
+  "provenance"
+]
```
First observedAug 17, 2026

TDQS

A3.8/5.0

Behavior3/5

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

Annotations already provide readOnlyHint: true, openWorldHint: true, idempotentHint: true, and destructiveHint: false. The description adds that the data comes from 'Vigi-Sky APIs' (external dependency) and that it is 'Live' (real-time), which is useful context beyond annotations. However, it does not disclose rate limits, data freshness guarantees, or any specific behavior of the API calls.

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 a single 12-word sentence that is front-loaded with the core purpose ('Live solar/CME context') and provides the source ('from Vigi-Sky APIs'). Every word earns its place; there is no redundancy or fluff.

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

Completeness4/5

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

Given zero parameters and an existing output schema (which presumably defines the return structure), the description is sufficient. It names the two main data categories (solar/CME context and Kp) and the source. It could be slightly more specific about what 'solar/CME context' includes (e.g., flares, CMEs), but the output schema likely covers that, so completeness is adequate.

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?

There are no parameters (input schema is empty), so per the guidelines baseline is 4. The description adds meaning by explaining what the tool returns (solar/CME context and Kp), which compensates for the lack of parameters. The schema coverage is trivially 100% as there are none.

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 provides 'Live solar/CME context plus current Kp', using a specific verb ('Live') and naming the specific resource (solar/CME context and Kp index). It distinguishes from siblings like 'aurora' (which likely focuses on aurora forecasts) and 'observation_conditions' (broader conditions) by focusing on solar activity and geomagnetic index.

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?

No explicit guidance on when to use this tool versus alternatives. Siblings include 'aurora' and 'observation_conditions', which might overlap, but the description does not provide any when-to-use or when-not-to-use advice. The agent is left to infer from the tool name and description alone.

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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