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trigger_bulk_embeddings

Enqueues bulk embedding generation for all StarSystem or CelestialBody records, with an option to process only records that are missing embeddings.

Instructions

Enqueue bulk embedding generation for all StarSystems or CelestialBodies.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "model_type": "<model_type>"
    },
    "name": "trigger_bulk_embeddings"
  }
}

Input Schema

NameRequiredDescriptionDefault
model_typeYesEntity type to generate embeddings for: StarSystem or CelestialBody
only_missingNoIf true, only generate embeddings for records that are not yet embedded

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. "Enqueue" hints that this is an asynchronous queued operation, but the description does not explain permissions, idempotency, what happens to already-embedded records, or how progress/results are tracked.

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?

It is a single clear sentence with no unnecessary wording, and the core action is front-loaded.

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

Completeness2/5

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

For a bulk job-triggering tool with no annotations and no output schema, the description is under-specified. It should indicate that the call enqueues rather than completes work, and ideally point to job-status tracking or describe the queued-job result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for both parameters, including the model_type enum and the only_missing default. The description itself adds no parameter detail beyond the schema, so the baseline of 3 applies.

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 states a specific verb ("Enqueue") and resource ("bulk embedding generation") and scopes it to "all StarSystems or CelestialBodies." This distinguishes it reasonably well from singular embedding-generation siblings, though it does not explicitly name those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by "bulk" and "all," suggesting this is the tool for mass embedding generation rather than individual records. However, there is no explicit when-to-use guidance, no exclusion conditions, and no named alternative for gap cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.