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@placraftic/mcp-server

@placraftic/mcp-server

by placraftic
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

update_order_status

Transition an order to a new Kanban stage and dispatch studio timeline events to keep production status and tracking synchronized.

Instructions

Transition an order to a new Kanban stage and dispatch studio timeline events

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "orderId": "<orderId>",
      "status": "<status>"
    },
    "name": "update_order_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
statusYesTarget Kanban status: 'pending', 'confirmed', 'printing', 'post_processing', 'ready', 'shipped', 'completed', or 'cancelled'
commentNoOptional operator comment or internal reason for the status transition
orderIdYesUnique numeric ID of the order

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It hints at a side effect worth knowing ('dispatch studio timeline events'), but does not say whether transitions are validated (e.g. cancelled -> pending), whether notifications fire, whether the change is reversible, or what represents failure. The one side-effect note is useful but insufficient.

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?

A single front-loaded sentence with no filler; the verb and object lead. It is compact, though the 'dispatch studio timeline events' clause is somewhat jargon-heavy and unattributed.

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?

This is a mutation tool with no annotations and no output schema, so the description must explain validation, side effects, and error behavior. It mentions an event dispatch but omits transition rules, notification recipients, and return/error semantics, leaving it under-specified for a state-changing operation.

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 100%, with the status enum and comment/orderId fully documented inline, so the baseline is 3. The phrase 'Kanban stage' loosely maps to the status enum but adds no syntax or constraint detail beyond the schema.

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?

States a specific verb+resource: 'Transition an order to a new Kanban stage'. An agent can tell this is a status-change operation, not a general field update. However, it never distinguishes itself from the sibling 'update_order', leaving the boundary between the two to inference.

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 update_order, cancel_order, or a bulk order edit. No prerequisites, allowed source states, or exclusions are stated, so the agent must guess the appropriate context.

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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