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KuudoAI

Amazon Selling Central MCP

by KuudoAI

Feeds_createFeedDocument

Create a feed document for a specified feed type to prepare and upload feed content to Amazon Selling Central.

Instructions

Catalog entry. Runs in your Kuudo deployment, not here. Creates a feed document for the feed type that you specify.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool creates a feed document and runs in the Kuudo deployment, but does not disclose side effects, required authentication, return values, or what happens when invoked. For a create operation with zero annotation coverage, this is a significant gap.

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 short and mostly to the point, using three sentences. The main action is clearly stated, and there is minimal waste. However, 'Catalog entry' is vague and not front-loaded with the most useful information; the actual purpose sentence appears after two contextual fragments.

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

Completeness2/5

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

Given no annotations, no output schema, and an empty input schema, the description is incomplete for a create-style tool. It does not explain the relationship to Feeds_createFeed, the required feed type parameter, the response format, or any preconditions. An agent would not have enough information to call this tool correctly with confidence.

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 input schema is effectively empty with zero defined properties and additionalProperties allowed, so the description adds the only semantic hint: a feed type must be specified. Since there are no formal parameters documented in the schema, the baseline is high, and the description provides at least one meaningful parameter-related clue, even if it lacks details about the parameter name or allowed values.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Creates a feed document for the feed type that you specify.' This makes the core operation clear and distinguishes it from sibling tools like Feeds_createFeed by naming 'feed document' as the resource. However, it does not explicitly differentiate itself from related Feeds tools beyond that noun, and the opening 'Catalog entry' is cryptic.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as Feeds_createFeed, Feeds_getFeedDocument, or Feeds_getFeeds. The phrase 'Runs in your Kuudo deployment, not here' gives deployment context but not selection guidance. The description does not explain the expected workflow or prerequisites, leaving an agent to infer when this tool is appropriate.

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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