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by net.crawlora
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yahoo_shopping_store

Read-only

Fetch current Yahoo Shopping deals for one retailer, with product and price details plus direct retailer URLs. Use yahoo_shopping_stores to discover retailer pages, or yahoo_shopping_category for editorial stories rather than offers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "store": "<store>"
    },
    "name": "yahoo_shopping_store"
  }
}

Input Schema

NameRequiredDescriptionDefault
storeYesRetailer slug from GET /yahoo-shopping/stores

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / store / description
      Added value: +"Retailer slug from GET /yahoo-shopping/stores"
  2. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is carried. The description adds useful behavioral context: the data is 'current' (freshness) and the payload includes product/price details plus direct retailer URLs. It stops short of pagination, rate limits, or auth notes, so a 3 is appropriate given the lower bar annotations set.

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: the core action is front-loaded, then a routing clause pointing to alternatives. Every clause earns its place with no filler.

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 an output schema present, the description need not explain return values, and it correctly covers purpose plus sibling routing. It is nearly complete for a one-param read tool; only minor operational details (pagination, freshness semantics) are absent, which the output schema may partly cover.

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% and the single 'store' parameter is documented in the schema as a retailer slug from GET /yahoo-shopping/stores. The description only implies a single retailer ('one retailer'), adding no syntax or format detail beyond what the schema provides, so the baseline 3 stands.

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?

States a specific verb (Fetch) and resource (current Yahoo Shopping deals for one retailer) plus the return content (product and price details plus direct retailer URLs). An agent can distinguish it from yahoo_shopping_stores and yahoo_shopping_category without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names two sibling alternatives with the condition that selects each: yahoo_shopping_stores to discover retailer pages, yahoo_shopping_category for editorial stories rather than offers. When-to-use and when-not-to-use are both covered.

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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