Syncretica MCP Server

trigger_bulk_embeddings

Enqueue bulk embedding generation for all God or Myth records, optionally limited to entries that are not yet embedded.

Instructions

Enqueue bulk embedding generation for all Gods or Myths.

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

Name	Required	Description	Default
`model_type`	Yes	Entity type to generate embeddings for: God or Myth
`only_missing`	No	If true, only generate embeddings for records that are not yet embedded

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Nov 13, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are present, so the description bears the full disclosure burden. 'Enqueue' usefully signals asynchronous job creation, but the description never says whether a job handle is returned (e.g., to use with get_job_status), whether existing embeddings are overwritten, whether the operation is idempotent, or how long it may take.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single well-formed sentence with the verb and resource front-loaded and no filler. It is efficient, though its brevity contributes to the gaps in usage and behavioral detail.

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 an asynchronous bulk mutation with no annotations and no output schema, an agent needs to know what happens after enqueueing (job tracking via get_job_status) and whether re-running is safe. Neither is covered, leaving the description thin relative to the tool's operational complexity.

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?

Schema description coverage is 100%, so both model_type and only_missing are already fully documented with an enum and a default. The description adds nothing beyond restating that the target is 'Gods or Myths', so the schema does the heavy lifting and baseline 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?

Specific verb ('Enqueue') and resource ('bulk embedding generation') with the entity scope ('all Gods or Myths') made explicit. The bulk framing implicitly contrasts with the singular generate_god_embedding/generate_myth_embedding siblings, but no sibling is named, so the agent must infer the distinction from the word 'bulk' alone.

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?

There is no explicit statement of when to pick this over generate_god_embedding/generate_myth_embedding, nor any prerequisites, cost, or follow-up guidance. The only cue is the word 'bulk', which leaves the agent to infer usage conditions.

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