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product_analysis

Destructive

Analyze products by providing a free-text objective and optional JSON inputs, returning domain-agent insights for decision-making.

Instructions

Run the product domain agent action product_analysis.

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

C2.1/5.0
Behavior2/5

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

The description adds scope context (JWT, tenant, company) but does not disclose behavioral effects beyond annotations. Given destructiveHint=true and readOnlyHint=false, an agent gets no warning that invoking this action may mutate or destroy state.

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 description is short and well-organized with an Args block and no unneeded prose. However, the first sentence is redundant with the tool name, and the brevity comes at the cost of meaningful semantic content.

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?

An output schema exists, so return values need not be described, but the tool is a generic domain-agent dispatcher with two free-form parameters and no usage context. The description leaves an agent unable to determine what objectives are appropriate, how to structure inputs, or what side effects may occur.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the two parameters. It defines message as 'Free-text objective' and inputs as 'Optional JSON string of structured inputs', which is minimal and lacks any concrete content, format, or examples.

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

Purpose2/5

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

The description says 'Run the product domain agent action `product_analysis`' — the verb+resource merely restates the tool's own name. It does not describe what product analysis actually does or how it differs from siblings like commerce_product_analysis or product_chat.

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. The routing sentence explains mechanism ('Routes through the platform's domain-agent dispatcher') but not selection criteria, exclusions, or preferred contexts.

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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