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Sibyl

Sibyl

by hello-emrah
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

embed

Create vector representations for texts using Gemini, store them in a JSON file, and return the file path and dimensions.

Instructions

Create embedding vectors for one or more texts with Gemini. Writes the vectors to a JSON file and returns the path and dimensions.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "embed"
  }
}

Input Schema

NameRequiredDescriptionDefault
textNoA single text to embed.
modelNo
textsNoMultiple texts to embed in one call.
output_pathNoWhere to write the JSON (defaults under the output dir).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the side effect of writing to a JSON file and the return of path and dimensions, but does not mention overwrite behavior, authentication needs, or potential errors. Partial transparency.

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?

Two concise sentences: the first states the purpose, the second states the side effect and return value. Every word earns its place, with no redundancy.

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?

No output schema exists, so the description must explain return values – it does (path and dimensions). It covers the core workflow well but omits the 'model' parameter and details about the JSON file contents. Overall sufficient with minor gaps.

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 coverage is 75% (text, texts, and output_path have schema descriptions). The description adds the 'one or more texts' clarification but does not explain the 'model' parameter or output_path default beyond the schema. Provides marginal added value.

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 uses a specific verb 'Create' with a clear resource 'embedding vectors' and scope 'for one or more texts with Gemini'. It clearly distinguishes from sibling tools which are about image/video generation, speech, or research.

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

Usage Guidelines4/5

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

The description provides clear context that this tool is for embedding texts, which is enough given no sibling tool handles embeddings. It doesn't explicitly state when not to use it, but the context is unambiguous and no alternatives exist.

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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