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Create product kit in Paired Plus

paired_plus_create_product_kit
Read-onlyIdempotent

Create product kit in the user's own Paired Plus account from ChatGPT, Claude or any AI agent. Returns how to do it in Paired Plus step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Paired Plus Cloud Browser. Paired Plus's official API: The ProSolutions Paired host publishes API help, but no self-serve API key or onboarding guide was found.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "paired_plus_create_product_kit"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Strong disclosure beyond the annotations: it explicitly says it 'opens nothing by itself' and returns screens, buttons and fields, which reconciles the create-sounding name with readOnlyHint=true. The closing note about the official API and the absence of a self-serve API key is opaque in its relevance and slightly muddies an otherwise clear behavioral picture.

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

Conciseness3/5

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

The purpose and the 'opens nothing by itself' correction are front-loaded, which is right. But the definition crams three unrelated ideas into two long sentences, and the trailing API/API-key sentence adds length without actionable meaning.

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?

With no parameters and no output schema, the description carries the burden of explaining what comes back, and it does: step-by-step screens, buttons and fields, plus the required follow-up tool family. What is missing is how detailed or account-specific those steps are and whether the result is reusable across agents.

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 zero parameters at 100% coverage, so the baseline applies and there is nothing for the description to disambiguate. It does not waste words re-explaining an empty input object.

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 (create a product kit in the user's Paired Plus account) and clarifies the surprising part: the tool returns step-by-step instructions rather than executing anything. It does not differentiate itself from near neighbors like paired_plus_manage_product or the other paired_plus_create_* tools, so an agent must infer the boundary itself.

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?

Usage is implied rather than stated: the reader learns the intended workflow chain (call this to get the steps, then act via cotlet_browser_* in the Cloud Browser). There is no explicit 'use this instead of X when Y' guidance and no precondition or exclusion, so the agent has to infer when this is the right entry point.

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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