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seelig.ai booking

Request an order

request_order
Destructive

Prepares an order or quote request for one service with the person's own details and the totals from quote_order. Sends the person a confirmation email, which cannot be unsent. Nothing is ordered and no terms are accepted until the person opens the link, reads the terms and confirms.

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": {
      "offer": "<offer>",
      "fields": "<fields>",
      "expected": "<expected>"
    },
    "name": "request_order"
  }
}

Input Schema

NameRequiredDescriptionDefault
langNode
offerYesOrderable service id
choiceNo
fieldsYesThe buyer's answers, keyed by the field names quote_order returns in form.fields
expectedYesThe totals from quote_order that the person saw and agreed to

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations declare destructiveHint=true and idempotentHint=false, and the description adds genuinely new context: a confirmation email is sent that 'cannot be unsent', and nothing is ordered nor terms accepted until the person opens the link and confirms. This tells the agent the action is irreversible at the email level but not yet a binding order, which annotations alone could not convey.

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?

Three short sentences, each doing distinct work: what it builds, the irreversible side effect, and the legal/state guarantee. The irreversible email is front-loaded right after the purpose rather than buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive, non-idempotent, nested-object tool this covers the state machine well (prepared → emailed → confirmed) and the safety implications. With no output schema, though, it never says what the call returns (link, request id, status) or what happens on duplicate calls, leaving the agent to guess at the response shape.

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 coverage is 60%, with offer and fields and expected partly documented inline. The description clarifies that 'fields' are the person's own details and that 'expected' carries the quote_order totals, but it says nothing about lang, choice (tier/extras/groups/monthly), or validation behavior, so it only marginally extends the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Prepares an order or quote request') plus scope ('for one service'), and ties itself to the sibling tool quote_order as the source of totals. An agent can distinguish it from quote_order and request_booking without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The prerequisite chain is explicit: the request is built from the totals returned by quote_order and the buyer's answers, so the agent knows this is the step after quoting. It does not state exclusions or contrast itself with request_booking, so routing between the two request-flows still requires inference.

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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