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Webotee Amazon Product Research

find_sourcing_opportunities

Read-only

Analyze an Amazon ASIN to identify viable sourcing opportunities across private label, wholesale, and arbitrage models with honest viability assessments and risk analysis.

Instructions

Given an Amazon ASIN, diagnose its business model (private-label / wholesale / arbitrage) and find real-world supplier, wholesale and arbitrage matches across the web, then return an HONEST sourcing read: a viability qualifier (green/yellow/red), the specific move + required differentiation, conservative economics, named risks (IP, tariffs, MOQ, saturation, gating, dropship policy) and validation steps. A credible lead generator, not get-rich advice. Scout+.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesThe Amazon ASIN (10 chars).
marketplace_idNoMarketplace (2 = US). Default 2.
Behavior4/5

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

Annotations provide readOnlyHint=true, which is consistent with the description. The description adds behavioral detail about the output (viability qualifier, risks, validation steps) and states it provides 'honest' sourcing advice, not get-rich-quick promises. This goes beyond the annotation by describing the nature and tone of the results.

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?

The description is a single paragraph that front-loads the core purpose and then details the output. It is reasonably concise for the amount of information conveyed, though it could be slightly tighter. Every sentence adds value, with no wasted words.

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 the tool's complexity (diagnosing business model, returning a detailed assessment) and no output schema, the description covers the key aspects: input, process, and output format (viability qualifier, risks, etc.). It lacks specifics on data freshness or exact JSON structure but is sufficient for an agent to understand what the tool does and what it returns.

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% for both parameters (asin and marketplace_id). The description mentions 'Given an Amazon ASIN' but does not add significant new meaning beyond what the schema provides. Baseline of 3 is appropriate as the description does not compensate for missing schema details.

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 clearly states the tool's purpose: given an ASIN, diagnose business model, find supplier matches, and return a sourcing read with viability qualifier, differentiation, economics, risks, and validation steps. It distinguishes itself from siblings like 'evaluate_asin_sourcing' or 'alibaba_supplier_search' by emphasizing an honest, comprehensive lead generation output.

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 implies usage when an ASIN is available and a detailed sourcing analysis is needed, but it does not explicitly state when to use this tool versus alternatives (e.g., 'evaluate_asin_sourcing' or 'search_products'). No guidance on when not to use or prerequisites.

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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