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AisleNode Local Commerce (Meta Muse & Claude MCP)

search_catalog

Search real-time physical retail store inventories near a shopper’s GPS location. Returns verified brick-and-mortar stores, in-stock products, unit prices, and Haversine distance in kilometers.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of matching products to return (default: 10)
queryYesProduct name, category, or keyword (e.g. "coffee", "milk", "usb cable")
customer_latNoShopper latitude coordinate for proximity ranking (optional)
customer_lngNoShopper longitude coordinate for proximity ranking (optional)
max_distance_kmNoMaximum search radius in kilometers (default: 15)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the disclosure burden. It usefully states that results are real-time, verified brick-and-mortar stores with in-stock products, unit prices, and Haversine distance, though it omits operational details such as rate limits, auth needs, or pagination behavior.

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 two efficient sentences with the core purpose front-loaded and no wasted wording. It immediately communicates the search scope before listing return details.

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?

With a fully described schema but no output schema, the description adequately explains the tool's purpose and return contents. A small gap remains around how proximity ranking behaves when optional customer_lat and customer_lng are omitted.

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 description coverage is 100%, so all five parameters are already documented in the input schema. The description reinforces the GPS-proximity nature of the search but adds no syntax or format detail beyond what the schema provides, making the baseline 3 appropriate.

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 states a specific verb and resource: searching real-time physical retail store inventories near a shopper's GPS location. It clearly distinguishes this product/store search from sibling tools such as create_order and check_order_status.

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 the use case through 'near a shopper's GPS location' and 'physical retail store inventories,' but it does not explicitly say when to use this tool versus alternatives or when not to use it. No sibling tool is named as a contrast.

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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