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NLACE-COM

mcp-supermercados-cl

by NLACE-COM

Listas guardadas del usuario

get_saved_lists

Fetches saved shopping lists from the user's Jumbo account, converting raw list data into a structured format with id, name, and items.

Instructions

Devuelve las listas de compra guardadas del usuario en la cadena, normalizadas a { id, name, items[] }. Requiere sesión: ejecuta el browserSnippet (GET /lists) en una pestaña YA LOGUEADA de www.jumbo.cl y pásame el JSON en rawLists. Para el detalle con items, repite el fetch a /lists/{scope}/{idList}. NO rasques el DOM ni React; es una llamada JSON directa. El servidor nunca maneja credenciales.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
storeNoCadena. Fase 2: jumbo.jumbo
branchIdNoSucursal de la sesión, ej. "jumboclj512".
rawListsNoJSON crudo de las listas del usuario (una lista con items[], o un arreglo de listas) que obtuvo el navegador.
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses the need for a logged-in session, direct JSON call, prohibition of DOM scraping, and that the server never handles credentials. This provides substantial behavioral context despite limited annotation support.

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

Conciseness3/5

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

The description is adequately structured with purpose first, then instructions. However, it is somewhat verbose, mixing instructions with warnings. It could be more concise while retaining key information.

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?

The description explains the user workflow, expected input format, and normalization of output. It also warns against scraping. Given the tool's complexity (external session), it covers most contextual needs, though error handling and edge cases are absent.

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 100% with descriptions for store, branchId, and rawLists. The description adds operational context (e.g., rawLists comes from a browserSnippet) but does not significantly deepen parameter meaning beyond what the schema already provides.

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 it returns saved shopping lists normalized to { id, name, items[] }. It provides a specific verb and resource. However, it does not explicitly distinguish this tool from siblings like get_frequent_purchases, which could be a similar retrieval tool.

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 explains the required session and browser workflow, implying when to use it (when lists are needed). However, it lacks explicit when-not-to-use or comparison to alternative tools, leaving some ambiguity about exclusivity.

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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