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create_price_monitor

Watch an ASIN and alert the user when its price drops to the target. Call when the user says things like 'watch this' or 'alert me if it goes below £20'. source is the marketplace: Amazon UK, Amazon DE, Amazon IT, Amazon ES, Amazon FR, Amazon US or Amazon Business UK.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinYes
sourceNoAmazon UK
target_priceYes

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It mentions alerting and the source parameter, but does not clarify persistence (e.g., does it create a recurring monitor?), side effects, or prerequisites beyond the example phrases. Partial transparency.

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

Conciseness5/5

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

Two efficient sentences: first states core purpose, second gives usage triggers and parameter clarification. No fluff, front-loaded, every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description lacks return value info, prerequisites (valid ASIN?), and any rate limits or authentication needs. It covers the essentials but leaves gaps for an agent to infer.

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?

The schema has 0% coverage, so the description must add meaning. It explains the 'source' parameter fully by listing marketplaces, and the example implies 'target_price' is a number and 'asin' is a product identifier. This adds value beyond the schema's bare property names.

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 states a specific verb ('Watch... and alert') and resource ('ASIN'), and clearly differentiates from sibling tools like 'add_storefront_monitor' or 'get_price_monitors' by focusing on creation with a price target.

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 examples ('watch this', 'alert me if it goes below £20'), giving clear context for when to call the tool. However, it lacks explicit statements of when not to use or alternatives.

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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TDQS

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct data type or action (e.g., product analysis, deal types, FBA operations). Even similar-sounding tools like get_deal_results and get_oa_deals are clearly separated by domain (A2A vs OA) in descriptions. No significant overlap.

Naming Consistency5/5

All tools follow a clear verb_noun pattern with underscores (e.g., analyse_product, create_deal_task, get_credits). The consistent 'get_' prefix for retrieval tools and varied but predictable action verbs make the set easy to navigate.

Tool Count4/5

At 37 tools, the set is large but covers a broad Amazon seller ecosystem (research, sourcing, FBA, deals, monitoring). Each tool serves a distinct purpose, and the count reflects the domain's complexity without being bloated.

Completeness5/5

The tool surface covers all major seller workflows: product analysis, profit calculation, sourcing, deal discovery, storefront monitoring, FBA operations, purchase tracking, price alerts, and reconciliation. No obvious gaps for core tasks.

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