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product_trend_synthesis

Destructive

Synthesize product trends by submitting a free-text objective and structured inputs. Get actionable insights to guide product strategy.

Instructions

Run the product domain agent action trend_synthesis.

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 discloses that the tool routes through the platform's domain-agent dispatcher under JWT, tenant, and company scope, which adds useful auth/scoping context. Annotations already communicate the destructive, non-idempotent nature, so the description does not need to repeat that. It does not add details about side effects, but the annotations carry that burden.

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, front-loaded with the core purpose, and structured with a clear Args section. Every sentence serves a function with no filler.

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 description is minimally complete given the output schema and annotations: it identifies the action, scoping, and both parameters. However, it lacks an explanation of what trend synthesis does and when to invoke it over sibling domain-agent tools, leaving selection somewhat ambiguous.

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?

The input schema has no property descriptions, so the Args section provides minimal semantics: `message` is a free-text objective and `inputs` is an optional JSON string. This is helpful but shallow; it does not describe expected JSON structure, how the two parameters interact, or example usage.

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 action: `Run the product domain agent action 'trend_synthesis'`. It identifies the resource and domain, which helps distinguish it from similar commerce_trend_synthesis. However, it does not explain what the trend synthesis action actually does, relying on the tool name for semantic meaning.

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 like commerce_trend_synthesis, product_chat, or dispatch_domain_agent. The routing details explain mechanics but not selection criteria or exclusions.

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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