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royaltea-public

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Calculate Revenue Split

calculate_revenue_split
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Model real take-home from a game/app sale, end to end: apply the storefront/platform cut (Steam tiers, Epic 0%-then-12%, Epic First Run, Apple/Google small-business rates, console, itch) and optional Unreal royalty, publisher cut, and expenses — THEN split the remaining contributor pool fairly by each person's relative contribution. This is the accurate way to answer 'if we make $X on , what does each person actually take home'. No account needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
revenueYesGross revenue / player spend to model (e.g. 50000)
expensesNoOptional costs to subtract before the contributor pool (marketing, tools, etc.)
platformNoStorefront the revenue comes from. Omit if the money is already net of platform fees.
contributorsYesThe people sharing the contributor pool. `points` is a relative weight (bigger = larger share); if you only know rough effort, use 1-10.
publisherCutNoOptional % a publisher takes off the top after platform fees (0-100)
unrealEngineNoGame built on Unreal Engine? Applies the 5% royalty on gross above $1M lifetime (waived on Epic).
lifetimeGrossNoLifetime gross so far (for the Unreal $1M royalty threshold). Default 0.
poolPercentageNo% of net revenue that goes to the contributor pool vs staying with the studio (default 100)
lifetimeRevenueNoRevenue already earned on this platform in the tiering period (drives Steam $10M/$50M tiers and Epic/Apple/Google $1M thresholds). Default 0.
platformCutOverrideNoFor itch/direct: the storefront cut fraction 0-1 (e.g. 0.05).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description does not contradict. It adds useful context like 'No account needed' and 'end to end' processing, but does not elaborate on rate limits or data persistence.

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 two sentences, front-loaded with the core purpose, and every clause adds essential context. No unnecessary words.

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?

Given the tool's complexity (10 parameters, no output schema), the description explains the end-to-end flow and the role of key parameters. It lacks explicit mention of return format (e.g., per-contributor amounts), but the overall process is well-covered.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining domain terms (e.g., Steam tiers, Epic First Run) that clarify platform enum choices, and gives a holistic overview of how parameters combine (platform cut, royalty, publisher cut, expenses, then split).

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 clearly states the tool models real take-home from a game/app sale end-to-end, specifying the action (calculate) and resource (revenue split). It distinguishes from siblings by emphasizing it's the 'accurate way' to answer per-person take-home.

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 provides clear context (modeling take-home for a given platform), but does not explicitly state when not to use or mention alternatives. The purpose is well-defined, so the omission of explicit exclusions is minor.

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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