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memory_set

Store persistent data values with unique keys for AI agents using the mcp-toolkit server. Save text, numbers, lists, or JSON objects to memory for later retrieval.

Instructions

Guarda un valor en memoria persistente bajo una clave.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyYesNombre único de la clave (ej: "usuario_preferencias").
valueYesValor a guardar. Puede ser texto, número, lista u objeto JSON.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it indicates this is a write operation ('Guarda'), it doesn't mention persistence characteristics (e.g., durability, expiration), permissions required, or potential side effects. This leaves significant gaps for a mutation tool.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded with the core functionality.

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

Completeness3/5

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

Given that this is a mutation tool with no annotations but with a complete input schema and an output schema (which handles return values), the description is minimally adequate. However, it lacks important behavioral context about persistence and side effects that would be expected for a storage operation.

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 schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't clarify key uniqueness constraints or value serialization details). Baseline 3 is appropriate when the schema does the heavy lifting.

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 action ('Guarda un valor') and resource ('en memoria persistente bajo una clave'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like memory_get or memory_delete, which would require a 5.

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 like memory_get (for retrieval) or memory_delete (for removal). It states what the tool does but offers no context about appropriate use cases or exclusions.

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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