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Create Promo Profile

create_promo_profile

Create a reusable discount PROFILE on a live event — a shared per-tier discount config (tiers: ticket_class_id → percent/fixed) that MANY promo codes attach to, with optional max uses + schedule. For a single coupon or discount code, use create_promo_code instead. Counts against your plan's discount-profile cap. Requires event_id + tiers; you must be a host.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tiersYes
event_idYes
max_usesNo
starts_atNo
expires_atNo
profile_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / tiers / additionalProperties / properties / discount_value / exclusiveMinimum
      Removed value: -0
    • addedInput schema / properties / tiers / additionalProperties / properties / discount_value / minimum
      Added value: +0
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the mutation/safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false). The description adds genuinely non-obvious context beyond that: it counts against the plan's discount-profile cap, requires host permission, and requires event_id + tiers. It stops short of describing return/rollback behavior, so 4 is fitting.

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?

Front-loads the core action and definition, then ordering alternatives, quota impact, and requirements. Dense but every clause contributes; the em-dash definition and cap emphasis are efficient. Slightly heavy, hence 4 rather than 5.

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 mutation tool whose annotations cover safety and with no output schema, the description is nearly complete: requirements, dependency alternative, quota, permission, and tier structure are all present. Missing only minor details like profile_name semantics and scheduling behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description carries the burden and delivers: it marks event_id + tiers required, clarifies tier keys are ticket_class_ids (which schema propertyNames does not), and notes percent/fixed plus optional max_uses and schedule. It omits profile_name and the starts_at/expires_at split, so not a perfect 5.

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 (Create) and resource (reusable discount PROFILE), and clarifies the conceptual distinction from sibling create_promo_code by explaining it is a shared config that many codes attach to. An agent can distinguish it from create_promo_code without opening either schema.

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?

Explicitly names the alternative and the selecting condition: 'For a single coupon or discount code, use create_promo_code instead.' It also states the context (on a live event, must be a host) and the plan-cap consequence, leaving little to 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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