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Junglescout Sales Estimate

junglescout_sales_estimate
Read-onlyIdempotent

How many units does an Amazon ASIN sell — returns Jungle Scout estimated units sold, revenue, and price for a product ASIN. Example: junglescout_sales_estimate({ asin: "B08N5WRWNW", marketplace: "us", _apiKey: "KEY_NAME:API_KEY" })

Input Schema

NameRequiredDescriptionDefault
asinYesAmazon Standard Identification Number, e.g. "B08N5WRWNW"
_apiKeyYesJungle Scout credential as "KEY_NAME:API_KEY" (both parts, colon-joined) from your Developer page. Requires the API add-on.
end_dateNoOptional range end, YYYY-MM-DD. Defaults to today.
start_dateNoOptional range start, YYYY-MM-DD. Defaults to ~30 days ago.
marketplaceNoAmazon marketplace country code (default "us"). One of: us, uk, de, in, ca, fr, it, es, mx, jp

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already cover readOnlyHint, idempotentHint, openWorldHint, and non-destructiveness, so the description does not need to restate those. It does add that the returned data is 'estimated' rather than exact, which is useful, but it does not mention rate limits, authentication failures, or approximation caveats. With annotations present, this is adequate but not enriched.

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?

The description is one focused sentence followed by a compact runnable example. It front-loads the core purpose and uses the example to illustrate the expected argument object without introducing unnecessary prose. Every element earns its place.

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?

For a read-only, idempotent tool with full schema coverage announced, the description plus schema together give an agent everything needed to invoke it correctly: the ASIN, marketplace key, API credential format, and optional date range. Since no output schema exists, the description usefully names the returned values (units sold, revenue, price). It could have added edge-case behavior (e.g., missing ASIN or invalid marketplace), but that is a minor gap.

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 description coverage is 100%, so the baseline is 3 and the description does not need to explain each parameter. The provided example demonstrates asin, marketplace, and _apiKey, but it adds no semantic meaning beyond the schema. The description does not clarify date-range behavior or marketplace options beyond what is already in the input schema.

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 action ('returns Jungle Scout estimated units sold, revenue, and price') and a specific resource ('product ASIN'), so an agent can immediately understand what the tool does. It is clearly distinct from sibling tools like junglescout_keyword_data, which would target keywords rather than ASIN-level sales metrics.

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 by explicitly focusing on Amazon ASIN sales estimates)Skip. It gives a concrete example of a correct call, but it does not state when to prefer this over junglescout_product_database or junglescout_keyword_data, nor does it mention any exclusions. The scope is clear enough for basic routing but lacks explicit 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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