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product_trend_synthesis

Synthesize product trends by submitting a free-text objective and optional structured inputs to the domain agent.

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
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions routing under JWT/tenant/company scope, which addresses authorization, but does not disclose side effects, rate limits, error behavior, or whether the action is read-only or mutating.

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 concise at three sentences plus an arg list. It front-loads the main purpose and uses clear structure. There is no redundancy or wasted words.

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?

Despite having an output schema (so return values are covered), the description lacks important context for a domain agent action. It does not explain what the action does, how to interpret results, or how this tool fits with siblings like commerce_trend_synthesis. The agent needs more completeness to use it effectively.

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 schema has 0% description coverage, but the description adds brief explanations for both parameters: 'message' is a free-text objective, and 'inputs' is an optional JSON string. This provides useful context beyond the raw schema, though it remains minimal.

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 the action is to run a specific domain agent action named 'trend_synthesis' for the product domain. However, it does not explain what 'trend_synthesis' accomplishes or how it differs from sibling tools like 'commerce_trend_synthesis', leaving some ambiguity about its specific purpose.

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 offers no guidance on when to use this tool versus alternatives, nor does it specify prerequisites or when not to use it. The agent is left without context to decide between this and similar trend synthesis tools across other domains.

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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