Paxaver

Discard Lunch Order Draft

discard_lunch_order_draft

DestructiveIdempotent

Permanently discards an unpaid draft order - the caller must own it and it must still be in draft status (order_id from create_lunch_order_draft). Nothing was ever charged, so there is no refund; the draft is simply deleted. For a finalized order use cancel_my_lunch_order instead. DESTRUCTIVE - confirm with the user before discarding.

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": {
      "order_id": "<order_id>"
    },
    "name": "discard_lunch_order_draft"
  }
}

Input Schema

Name	Required	Description	Default
`order_id`	Yes	Draft order ID from create_lunch_order_draft - must still be in draft status

Output Schema

Name	Required	Description	Default
`status`	No	Order status (discarded)
`orderId`	No	Discarded draft order ID

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 3, 2026
RemovedOct 2, 2026
AddedSep 19, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description provides substantial behavioral context beyond the annotations: the operation is permanent, no refund exists because nothing was charged, the draft is simply deleted, and it explicitly warns to confirm with the user. It also emphasizes destructive behavior, matching the destructiveHint annotation without contradicting it.

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?

The description is compact and front-loaded, with every sentence contributing necessary operational or safety information. The critical DESTRUCTIVE warning is included without redundancy or fluff.

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

Completeness5/5

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

For a single-parameter destructive tool, the description fully covers purpose, preconditions, side effects, alternatives, and user confirmation. Since an output schema exists, return-value details are not required here, and nothing essential is missing.

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 input schema already fully describes order_id as the draft order ID from create_lunch_order_draft and requires draft status. The description reinforces this but adds no new parameter meaning beyond what the schema already covers, so the baseline of 3 is appropriate.

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?

The description identifies a specific verb and resource: 'Permanently discards an unpaid draft order.' It also differentiates from the sibling tool by specifying that it applies only to drafts and directing finalized orders to cancel_my_lunch_order.

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

Usage Guidelines5/5

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

The description explicitly states when to use the tool: the caller must own the draft, it must still be in draft status, and it must be unpaid. It also names the alternative for finalized orders and includes a clear confirmation requirement, leaving no ambiguity about usage.

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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