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product_customer_segment

Destructive

Segment customers into groups by running the product domain agent action. Use free-text objectives and optional structured inputs to define the segmentation criteria.

Instructions

Run the product domain agent action customer_segment.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

The description adds useful behavioral context beyond annotations by disclosing that execution routes through the platform's domain-agent dispatcher under JWT, tenant, and company scope. However, it does not describe any side effects or caution around the destructiveHint=true annotation, leaving that entirely to the structured metadata.

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 appropriately short and front-loads the core purpose in the first sentence. The Args section is cleanly organized and adds the necessary parameter context without redundancy.

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?

The presence of an output schema means return values need no explanation, and both parameters are at least named. However, the action itself remains opaque: an agent still cannot tell what makes a good `message` or what structured `inputs` are valid for the customer_segment action, which is a meaningful gap for correct invocation.

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?

With 0% schema description coverage, the description carries the burden of explaining parameters. It provides minimal but functional explanations for both `message` and `inputs`, though it omits any detail about what structured inputs the customer_segment action expects or what format the JSON string should follow.

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 clearly states it runs the product domain agent action `customer_segment`, which identifies the exact operation and domain. It also distinguishes itself from direct API tools by specifying the domain-agent dispatcher routing, though it does not explain what customer segmentation actually does.

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?

The description gives no guidance on when to use this tool versus alternatives, such as `commerce_customer_segment`, `product_chat`, or other product domain tools. It only says it routes through the dispatcher, which is context but not usage direction.

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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