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Webotee Amazon Product Research

watchlist_add

Add identifiers (ASIN, brand, seller, niche key) to a watchlist. Records current state to enable future comparison and detect changes.

Instructions

Create or add to a saved tracking list the user can monitor over time. list_type is one of asin, brand, seller, niche; name is the user's label for the list; items are the identifiers to track (ASINs, brand names, seller names, or niche keys). Captures a baseline of the current observed state so a later 'what changed' check can show new sellers and score moves. Use when the user says 'track these ASINs', 'add Nike to my brand watchlist', 'start monitoring ...'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
list_typeYesasin | brand | seller | niche
nameYesThe list's label (e.g. 'Q4 arbitrage candidates').
itemsYesIdentifiers to add.
marketplace_idNoMarketplace (2 = Amazon US).
Behavior4/5

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

The description explains that capturing a baseline is part of the behavior, adding context beyond the annotation's readOnlyHint=false. It does not contradict annotations.

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 two sentences, front-loaded with the main action. It is informative without being verbose, though the first sentence is moderately long.

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 4 parameters, no output schema, and minimal annotations, the description adequately covers purpose, parameter context, and usage. Missing return value details, but overall complete enough for agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

While schema covers all parameters, the description adds meaning by explaining list_type values (asin, brand, seller, niche) and what items represent (ASINs, brand names, etc.), which is not in the schema descriptions.

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 creates or adds to a saved tracking list, with specific verb (create/add) and resource (watchlist). It distinguishes from sibling tools like watchlist_list (listing) and watchlist_remove (removing) by focusing on the add action.

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

Usage Guidelines5/5

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

Explicit usage guidance is provided: 'Use when the user says 'track these ASINs', 'add Nike to my brand watchlist', 'start monitoring ...''. This tells the agent exactly when to invoke this tool.

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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