B2A Fulfillment Factory

ebay_sold_listings_comps_scraper

Read-only

Price products against 90-day eBay and Mercari sold comps, median values, IQR spreads, sell-through, and net flip profit, with Deal Sniper alerts for underpriced listings.

Instructions

Fetch 90-day realized eBay and Mercari sold prices (including Accepted Best Offers), median sold valuation, IQR price spread, 90-day sell-through rate, net flip profit after 13.25% eBay / 10% Mercari fees, and real-time underpriced Deal Sniper alerts.

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": {
      "keywords": "<keywords>"
    },
    "name": "ebay_sold_listings_comps_scraper"
  }
}

Input Schema

Name	Required	Description	Default
`keywords`	Yes	Array of product SKUs, model names, or search keywords to price against 90-day sold comps (e.g. ['Sony A7IV Body Only'])
`condition`	No	Target item condition ('used', 'new', 'refurbished', 'parts')	used
`filterDealers`	No	Exclude commercial liquidator spam, empty-box listings, and broken parts from median valuation math
`underpricedThresholdPct`	No	Discount percentage below the 90-day median sold price (5 to 80%) required to trigger a Deal Sniper alert

Schema Changelog

Changes observed during successful MCP inspections.

Addedv1.2.0Nov 13, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already cover the read-only, open-world, non-destructive profile, so the description's job is to add behavioral substance — which it does by disclosing the 90-day lookback, inclusion of Accepted Best Offers, the exact fee models (13.25% eBay / 10% Mercari) used in profit math, and that alerts are real-time. It omits rate limits, latency, and any authentication or quota constraints, which keeps it below 5.

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

Conciseness4/5

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

It is a single front-loaded sentence with no filler, and the core resource (sold prices) appears first. It is dense and list-like, bordering on a run-on enumeration of metrics, but each clause adds a distinct capability rather than repeating structured data.

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 no output schema, the description carries the burden of explaining returns, and it does so thoroughly by naming every computed field. It is slightly incomplete on operational details such as result volume, pagination, or coverage limits of the 90-day window, preventing a 5.

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 four parameters (keywords, condition, filterDealers, underpricedThresholdPct) are already fully documented in the schema. The description adds no additional meaning about parameter behavior, so the baseline of 3 applies.

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 names a specific verb (fetch) and precisely enumerates the resources and derived metrics: 90-day eBay and Mercari sold prices including Accepted Best Offers, median valuation, IQR spread, sell-through rate, net flip profit, and deal alerts. This is far more specific than the tool name alone and no sibling tool overlaps this domain.

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 the content (resale pricing, flip profitability, deal hunting), but there is no explicit statement of when to use this versus other research tools, no prerequisites, and no exclusions. An agent can infer the scenario but is given no routing guidance.

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