> For the complete documentation index, see [llms.txt](https://docs.arkada.gg/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.arkada.gg/referral-system.md). # Referral System {% hint style="info" %} **This section is under development and may change over time.** {% endhint %} The Arkada Referral System rewards contributors who bring **active users** to the platorm — users who complete quests and meaningfully participate. Arkada is built on a simple principle: **quest completions are the single core signal of value**. Referral rewards are distributed **only when real participation happens**, not based on reach, hype, or promotional effort alone. The system is structured into **distinct layers**, each rewarding a different type of contribution. *** #### **User & Creator Referral Layers** These layers are designed for individual users, creators, influencers, and community leaders. * **Direct Referrals (Layer 1)** Reward contributors who onboard users that actively complete quests. * **Mentorship Rewards (Layer 2)** Reward contributors who onboard and support other contributors, stacking on top of direct referrals. * **Joint Pools (Layer 3)** Enable groups of contributors to earn collectively through shared performance and coordinated execution. All user-facing layers follow the same performance-based rules and operate within system-wide caps and safeguards. *** #### **Partner Campaign Structures** These structures are designed for projects, platforms, and ecosystems using Arkada as an engagement infrastructure. * **Featured Projects** Partners that work with Arkada to onboard users either by running dedicated quest campaigns **or by integrating Arkada into their existing distribution channels**. * **Ecosystems** Large networks of projects coordinating quests and distributing rewards through shared prize pools. These structures operate at a different scale and follow campaign-specific rules. *** #### **What Arkada Rewards** Arkada does **not** reward activity by default. Only **outcomes** are measured. **What is rewarded:** * Quest completions * Aggregate quest activity generated by referred users or teams **What is not rewarded directly:** * Impressions or reach * Number of posts * Follower count * Engagement without completed quests This ensures rewards are tied to **real participation**, not surface-level activity. *** #### **High-Level Reward Model** A predefined portion of platform value is allocated to contributors, while the remainder supports platform operations, development, and long-term sustainability. Across all referral layers: * **Maximum total share per individual: 40%** *(up to 30% from Direct Referrals + 10% from Mentorship)* * All rewards are drawn from the same shared allocation This keeps the system **fair, predictable, and sustainable**. *** #### **Transparency & Tracking** Every contributor has access to a **profile page** that serves as their referral control center. From this page, contributors can: * Access their unique referral link * Track quest-driven value generated * View performance by layer * Monitor progress toward the system maximum * Review historical performance All data is visible, verifiable, and updated in real time. *** #### **How It Works (Quick Start)** 1. Get your referral link from your profile 2. Share it with users 3. Users complete quests 4. Rewards are distributed automatically 5. Track everything in your profile *** **In short:** **If you bring users who complete quests, the system works for you.** Use the sections below to explore each layer in detail → --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.arkada.gg/referral-system.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.