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GolfData

by co.golfdata
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get_product

One product plus its enrichment_sources provenance rows. Every enriched field carries the source URL, confidence and checked_at it came from. Check enrichment_status before relying on specs: 'enriched' means model, release_year, msrp, description and specs are all sourced; 'partial' means some are missing.

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": {
      "product_id": "<product_id>"
    },
    "name": "get_product"
  }
}

Input Schema

NameRequiredDescriptionDefault
product_idYescanonical product uuid, from search_products

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It explains what the response contains, the provenance attributes on enriched fields, and the meaning of enrichment_status values, which is substantial context beyond the raw schema.

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?

Three focused sentences convey the core behavior, provenance model, and enrichment-status semantics without wasted words. The most important message, what the tool returns, is front-loaded.

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 single-parameter retrieval tool with no output schema, the description covers the key behavioral details: return scope, provenance fields, and status interpretation. Minor gaps like missing-product behavior are not critical given the low complexity.

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 already fully describes product_id as a canonical product UUID from search_products, and the description adds no parameter-specific detail. With 100% schema description coverage, the baseline of 3 is appropriate.

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 states a clear verb and resource: retrieving one product plus its enrichment provenance rows. It implies differentiation from siblings like search_products by emphasizing a single product and provenance detail, though it does not explicitly name alternatives.

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 gives valuable guidance about checking enrichment_status before trusting specs, which informs how to interpret results. However, it does not explicitly state when to choose this tool versus siblings like get_current_prices or get_verified_offers.

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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