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Webotee Amazon Product Research

collect_asin_now

Collect a live snapshot of an Amazon ASIN with current title, price, offers, sellers, and historical brand-seller intelligence. Returns today's data for a specific ASIN.

Instructions

Pull a LIVE, on-demand snapshot of a single Amazon ASIN right now — current title, price, live offers and the sellers on the listing today — and return it alongside Webotee's historical brand and seller intelligence, including the ASIN's product brand, title and price (or price range) and its fulfillment (FBA/FBM/AMZ). Use when the user gives a specific ASIN and wants its CURRENT/today's data rather than the pre-collected dataset (e.g. 'check ASIN B0... right now', 'who's on this listing today and at what price'). Amazon US only; one ASIN per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYesThe 10-character Amazon ASIN to collect live (US).
marketplace_idNoMarketplace (2 = Amazon US). US only.
Behavior3/5

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

With readOnlyHint=false in annotations, the agent already knows the tool is not read-only. The description adds the 'LIVE' and 'on-demand' qualifiers, implying a real-time API call with potential cost or rate limits. It does not explicitly disclose side effects like query limits or costs, but the annotations already carry the primary behavioral signal, so a score of 3 is appropriate.

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 three sentences and efficiently front-loads the purpose, data returned, and usage context. The first sentence is somewhat long (49 words) but no unnecessary repetition. It is structured logically: what it does, when to use, constraints. Slight verbosity prevents a 5.

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 no output schema, the description details the return data comprehensively (title, price, offers, sellers, historical intelligence, fulfillment). It also states constraints (US only, single ASIN). Missing operational details like error handling or rate limits, but the context provided is sufficient for agent decision-making.

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 input schema has 100% coverage with descriptions for both parameters (asin and marketplace_id). The description reinforces these by stating 'one ASIN per call' and 'Amazon US only,' but does not add new meaning beyond the schema. Baseline score of 3 is justified.

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 uses a specific verb 'pull' and clearly defines the resource as a single Amazon ASIN with live data. It explicitly lists the included data (title, price, offers, sellers, historical intelligence) and distinguishes itself from pre-collected datasets, making it distinct from sibling tools like asin_buybox_history or asin_profit_calc.

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

Usage Guidelines4/5

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

The description provides explicit usage context: 'Use when the user gives a specific ASIN and wants its CURRENT/today's data rather than the pre-collected dataset.' It gives example queries and constraints (Amazon US only, one ASIN per call). However, it does not mention alternative sibling tools by name, so guidance on when not to use is implicit rather than explicit.

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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