luma-mcp

luma_create_coupon_draft

Draft a coupon code with a discount percentage or fixed cents for a Luma event. Confirm to post.

Instructions

Stage a coupon. Nothing posts until confirm.

Pass exactly one of discount_percentage or discount_cents.

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": {
      "code": "<code>"
    },
    "name": "luma_create_coupon_draft"
  }
}

Input Schema

Name	Required	Description	Default
`code`	Yes
`extra`	No
`event_id`	No
`expires_at`	No
`description`	No
`discount_cents`	No
`max_redemptions`	No
`discount_percentage`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Jul 29, 2026

TDQS

A4.1/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that the action is a draft (stage) and does not post until confirm. This is the most important behavioral trait. It does not mention other aspects like idempotency or permissions, but for a draft tool this is adequate.

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?

Two sentences, both front-loaded. Every word adds value: 'Stage a coupon. Nothing posts until confirm.' and 'Pass exactly one of discount_percentage or discount_cents.' No filler, highly efficient.

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 8 parameters, 0% schema coverage, and no annotations, the description is minimal. The existence of an output schema (not shown) reduces the need to describe return values, but more guidance on how to use other parameters (e.g., event_id, expires_at) would improve completeness. Still, essential info for staging a coupon is present.

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 0% (no descriptions in input schema). The description adds value for two parameters (discount_percentage and discount_cents) by stating that exactly one must be passed. However, the other six parameters (code, extra, event_id, expires_at, description, max_redemptions) receive no additional explanation, leaving their semantics unclear.

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?

Description clearly states it stages a coupon and that nothing posts until confirm. It distinguishes from luma_create_coupon_confirm (the confirm counterpart). The constraint of passing exactly one discount field is highlighted, making the tool's purpose specific and unambiguous.

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 description specifies when to use: for staging a coupon before confirmation. It includes a critical usage rule: exactly one of discount_percentage or discount_cents. While it doesn't explicitly state alternatives, the sibling tool list provides context that luma_create_coupon_confirm is used after staging.

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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