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memorize_text

Store text passages and retrieve them later based on semantic meaning using local embeddings and vector storage.

Instructions

Memorize a text for later retrieval based on relevance in meaning, not just keywords.

Args:
    text (str): The text to memorize.
Returns:
    str: A message indicating success or failure of the operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes
metadataNo
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It indicates the tool memorizes text and returns a success/failure message, but omits details on persistence, side effects (e.g., storage location, data retention), and behavior with metadata. This is insufficient for a mutation-like tool.

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?

The description is very concise at two sentences plus args/returns, with no fluff. However, the conciseness comes at the cost of completeness; it could be slightly expanded to improve clarity without adding unnecessary length.

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?

The tool has 2 parameters, no output schema, and low complexity, but the description still falls short. It lacks usage context, error conditions, and differentiation from sibling tools. The return value is vaguely described as 'success or failure' without specifics, leaving gaps for an agent to use correctly.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. It merely restates that 'text' is the text to memorize, adding no semantic detail. The optional 'metadata' parameter is not described at all, leaving its purpose and format unexplained. The description adds negligible value beyond the schema.

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 clearly states the verb 'memorize' and the resource 'text', and adds a distinguishing feature: retrieval is based on relevance in meaning, not just keywords. However, it does not explicitly differentiate from sibling tools like memorize_multiple_texts or remember_similar_texts, leaving some ambiguity.

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 memorize_multiple_texts or remember_similar_texts. It lacks explicit when-to-use or when-not-to-use instructions, leaving the agent without context for tool selection.

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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