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SiteCheck Crypto & Finance

Finance Bstock

finance_bstock
Read-only

B-Stock wholesale liquidation auctions (US marketplace, all sellers): total live lots and 20 per page with listing id, title, storefront (seller), categories, condition, inventory type, units, pallets, manufacturers, current / opening bid, next minimum bid, number of bids, typical selling price, currency, start and end time, seller city/state/zip, shipment type, manifest flag, image and auction link. From bstock.com via a residential proxy. Price: $0.02 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

Input Schema

NameRequiredDescriptionDefault
pageNoResult page 1-40 (default 1)
categoryNoOptional: keep only lots whose categories contain this text, e.g. Cell Phones, Major Appliances

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior5/5

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

Excellent beyond-annotation disclosure: it states the source is a residential proxy, the exact pricing model ($0.02 USDC per successful call via x402 on Base, Solana or Arc), and that failed calls are not charged. This payment/auth behavior is critical for an agent and is not derivable from the readOnlyHint or openWorldHint annotations.

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

Conciseness3/5

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

The purpose and pricing details are front-loaded, but the middle is one long enumeration of roughly twenty return fields that duplicates the existing output schema. That enumeration consumes most of the description without adding value beyond structured data, making it longer than it needs to be.

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?

Given an output schema, complete annotations, and 100% schema description coverage, the description supplies the remaining essentials: the data source, payment model, and marketplace scope. It is nearly complete for calling the tool correctly, with only freshness or rate-limit details 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 coverage is 100%, and both parameters (page, category) are already fully described in the input schema. The description adds no extra meaning about these parameters – it only implies pagination via '20 per page' – so the baseline 3 applies.

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 clearly identifies the resource (B-Stock wholesale liquidation auctions, US marketplace, all sellers) and the returned data, so an agent can tell this is a marketplace-lot data retrieval tool. It lacks an explicit verb like 'fetch' or 'list', but the scope is unambiguous and clearly distinct from the crypto/finance pricing siblings.

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

Usage Guidelines2/5

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

The description gives context ('From bstock.com via a residential proxy') but never states when to choose this tool over alternatives or any exclusions. There is no guidance on how it differs from adjacent finance or scraper tools, leaving selection to inference.

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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