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commerce_supply_chain_analysis

Destructive

Analyze your commerce supply chain by providing an objective. Get actionable insights to identify issues and optimize performance.

Instructions

Run the commerce domain agent action supply_chain_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

B3.1/5.0
Behavior3/5

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

The description adds routing/scoping context beyond the annotations by stating the action goes through the domain-agent dispatcher under JWT, tenant, and company scope. It does not contradict the annotations; destructiveHint=true is consistent with an action that may mutate state, though the description does not elaborate on potential side effects.

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 compact and front-loaded with the action name, followed by routing context and a clear Args block. Every sentence serves a purpose, though more behavioral detail could be added without bloating it.

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?

For a generic agent-action invoker with a destructive hint and open-world hint, the description lacks important context: what the supply chain analysis action does, what effects it may have, what kind of message/inputs are expected, and when to choose this over related tools. The output schema helps with return values, but the decision and invocation context remains incomplete.

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?

Schema description coverage is 0%, so the description has to supply parameter meaning. It does identify message as a free-text objective and inputs as an optional JSON string, which is useful baseline information. However, it leaves the structure and accepted keys for inputs entirely unspecified.

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 names a specific action ('supply_chain_analysis') and says the tool runs it, so the verb-resource relationship is clear. However, it does not explain what supply chain analysis itself accomplishes, and it does not explicitly contrast itself with sibling commerce tools, so full differentiation is missing.

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 such as dispatch_domain_agent or other commerce_* tools. The description only mentions dispatcher routing and scoping, 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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