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commerce_trend_synthesis

Destructive

Analyze commerce data to synthesize trend insights. Provide your objective as a message and optional structured inputs to receive a synthesized trend analysis.

Instructions

Run the commerce 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

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false and destructiveHint=true, so the mutation/side-effect profile is known. The description adds the useful routing fact that the call goes through the platform’s domain-agent dispatcher under JWT/tenant/company scope, but it discloses no further side effects or operational caveats, so it stays at a 3.

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

Conciseness5/5

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

Four short sentences front-load the action name, then give routing context and an Args list without repetition or fluff. Every sentence earns its place.

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?

With no required parameters and an output schema present, the description doesn't need to explain return values. However, it leaves the actual behavior of `trend_synthesis` implicit and gives no selection guidance among the many commerce and synthesis siblings. An agent can invoke it, but may not be confident it is the right tool.

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?

Because schema description coverage is 0%, the description must carry this weight. It gives useful semantic labels: `message` is a free-text objective and `inputs` is an optional JSON string of structured inputs. That is better than the schema alone, but it remains thin—no expected keys, format details, or examples for `inputs`.

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 opening sentence names a specific verb (`Run`) and resource (`the commerce domain agent action `trend_synthesis``), so an agent knows exactly what operation this exposes. It doesn't describe what trend synthesis actually accomplishes or distinguish it from similar commerce siblings, so it falls short of a 5.

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?

No text explains when to use this tool versus alternatives like commerce_chat, commerce_predict, dispatch_domain_agent, or product_trend_synthesis. The only context is routing and scoping, so an agent has to infer when this is the appropriate choice.

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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