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Starlink Trains

starlink_trains
Read-onlyIdempotent

Recently launched Starlink trains (count + launch id).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
trainsNo
citationsYes
how_to_seeNo
provenanceYes

Schema Changelog

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

  1. Changed5 schema fields changed
    • removedOutput schema / properties / doctrine
      Removed value: -{
      -  "type": "string"
      -}
    • addedOutput schema / properties / how_to_see
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / provenance / properties / never
      Added value: +{
      +  "type": "string"
      +}
    • addedOutput schema / properties / trains
      Added value: +{
      +  "type": "array"
      +}
    • addedOutput schema / required
      Added value: +[
      +  "citations",
      +  "provenance"
      +]
  2. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, which clearly indicate a safe, read-only, potentially stateful operation. The description adds that it returns 'count + launch id', which is useful output context. However, it does not explain behavior over time (e.g., whether trains are ephemeral) or data freshness. Given the strong annotations, this is adequate.

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, concise sentence that captures the essence of the tool. Every word is meaningful: 'recently launched' sets context, 'Starlink trains' identifies the resource, and 'count + launch id' specifies the data fields. No wasted words.

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

Completeness3/5

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

Given the simplicity of the tool (0 parameters, well-covered by annotations) and the presence of an output schema (which describes return format), the description is mostly complete for basic understanding. However, it does not clarify whether 'recently launched' refers to days or weeks, nor does it explain if the tool filters by the user's location. With sibling tools like 'first_skies' and 'nights_network', the agent might benefit from more context on how this relates to actual visibility.

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 0 parameters and schema description coverage is 100%, so the description does not need to add parameter details. It mentions the specific data returned (count and launch id), which adds value beyond the schema of empty properties. This is a clear and helpful addition.

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

Purpose4/5

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

The description uses the verb 'launched' and specifies the resource 'Starlink trains', indicating a listing of recent Starlink train sightings. It mentions two data points (count and launch id) which clarifies the output. It does not explicitly differentiate from sibling tools like 'aurora' or 'iss_passes', but the resource name is distinctive enough.

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?

The description provides no guidance on when to use this tool versus alternatives such as 'nights_network' or 'iss_passes'. There is no mention of prerequisites, frequency of updates, or typical use cases. The context signals show 0 parameters, so the tool is simple, but the agent would benefit from knowing that this is for recently launched trains specifically.

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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