Skip to main content
Glama

NeuralVerge Business Intelligence

by ai.neuralverge.api
OverviewDiscussionsAdmin

Walmart product search

run_walmart_product_search

Search Walmart products by keyword: title, price, rating, and seller. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort by. Options: price_low = Price: low to high, price_high = Price: high to low, best_seller = Best seller, new = New arrivals, rating_high = Highest rated
keywordYesSearch term. e.g. wireless mouse
max_itemsNoMax items (up to 250) Default: 25.
max_priceNoMax price
min_priceNoMin price
start_pageNoStarting page Default: 1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed9 schema fields changed
    • changedInput schema / properties / keyword / description
      Previous value: -"Search term, e.g. 'wireless mouse'."New value: +"Search term. e.g. wireless mouse"
    • changedInput schema / properties / max_items / description
      Previous value: -"Maximum number of products to return (1-250, default 25). Billed at 1 point per returned record."New value: +"Max items (up to 250) Default: 25."
    • changedInput schema / properties / max_price / description
      Previous value: -"Maximum price, in USD."New value: +"Max price"
    • removedInput schema / properties / max_price / minimum
      Removed value: -0
    • changedInput schema / properties / min_price / description
      Previous value: -"Minimum price, in USD."New value: +"Min price"
    • removedInput schema / properties / min_price / minimum
      Removed value: -0
    • changedInput schema / properties / sort / description
      Previous value: -"Sort order (default best_match)."New value: +"Sort by. Options: price_low = Price: low to high, price_high = Price: high to low, best_seller = Best seller, new = New arrivals, rating_high = Highest rated"
    • changedInput schema / properties / sort / enum
      Previous value: -[
-  "best_match",
-  "price_low",
-  "price_high",
-  "best_seller",
-  "new",
-  "rating_high"
-]New value: +[
+  "price_low",
+  "price_high",
+  "best_seller",
+  "new",
+  "rating_high"
+]
    • changedInput schema / properties / start_page / description
      Previous value: -"Result page to start from (default 1)."New value: +"Starting page Default: 1."
  2. Added

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the billing model ('1 point per returned record'), which is real cost/pagination-related context, but says nothing about return format, rate limits, auth requirements, or how pagination interacts with billing.

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?

Two tight sentences with the core action front-loaded and the cost note second. No filler; every clause earns its place.

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?

For a keyword search tool with full schema coverage and no output schema, the description is nearly sufficient: it names the marketplace, the action, and returned fields. It could mention pagination/cost interaction, but nothing essential to invoking it correctly is missing.

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%, including enum values and defaults, so the schema already documents all six parameters. The description adds only the returned-field list, not parameter semantics, so the baseline 3 holds.

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?

States a specific verb (Search) and resource (Walmart products) with scope (by keyword) and enumerates what comes back (title, price, rating, seller). The marketplace name implicitly separates it from the many other *_product_search siblings, but it never explicitly distinguishes itself from run_walmart_product or the other marketplaces' search tools.

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?

Usage is implied by 'search by keyword' but there is no explicit when-to-use guidance, no exclusions (e.g. use run_walmart_product for a known item id), and no mention of alternatives. The agent must infer the context from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All NeuralVerge Business Intelligence toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources