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embed_documents

Convert an array of texts into semantic vector embeddings for batch processing, enabling similarity search and clustering.

Instructions

Получить эмбеддинги для массива текстов (batch).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoМодель эмбеддингов (text-search-doc, text-search-query)text-search-doc
textsYesМассив текстов для получения эмбеддингов
Behavior2/5

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

With no annotations, the description fails to disclose behavioral traits such as side effects, rate limits, authentication needs, or whether the operation is idempotent. It only mentions the basic action without any behavioral context.

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 sentence that conveys the core functionality concisely without extraneous information. It is front-loaded and efficient.

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?

Given the absence of an output schema and annotations, the description is insufficiently complete. It omits details about the return format, error behavior, and any constraints, leaving the agent without full context.

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% coverage for both parameters (model and texts), so the description adds no new semantic information beyond what the schema already provides. It meets the baseline but does not enhance understanding.

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 the tool's purpose: getting embeddings for an array of texts (batch). This distinguishes it from the sibling 'embed_text' which likely handles single texts, providing specific verb and resource.

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?

The description implies batch usage through the word 'batch' but does not explicitly state when to use this tool versus alternatives like 'embed_text'. No context on when not to use or prerequisites.

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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