> ## Documentation Index
> Fetch the complete documentation index at: https://protocol.crunchdao.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Coordinator FAQ

> Frequently asked questions about running and operating a Crunch as a Coordinator.

Get answers to common questions about designing, launching, and operating Crunches on the Crunch
Protocol.

<AccordionGroup>
  <Accordion title="What is a Coordinator?">
    Coordinators design, launch, and operate **Crunches** — prediction challenges that tap into a
    global network of ML engineers. As a Coordinator, you bring data, define the problem, and set
    incentives. Crunch Labs provides the infrastructure, model orchestration, and contributor network.

    See [What is the Crunch Protocol?](/overview/what-is-the-crunch-protocol) for a full overview.
  </Accordion>

  <Accordion title="What are the steps to launch a Crunch?">
    1. **Set up your local environment** — Install `crunch-node`, scaffold a workspace, and run `make deploy`
    2. **Define your prediction task** — Specify the model interface, data, and scoring function
    3. **Create a challenge package** — Publish the model interface as a PyPI package with quickstarters
    4. **Register on the protocol** — Create a Solana wallet and register through the Coordinator Platform
    5. **Wait for approval** — The Foundation approves your Coordinator status
    6. **Deploy** — Use the Coordinator Platform to push to testnet, then mainnet

    The full walkthrough is in the [Getting started](/getting-started/local-environment-setup) guide.
  </Accordion>

  <Accordion title="Can I run an ongoing (continuous) competition?">
    Yes. Coordinators can run two types of Crunches:

    **Continuous Crunches**

    * Predictions streamed in real-time
    * Checkpoints and payouts at regular intervals (e.g., weekly)
    * Ideal for price data, risk, or volatility forecasting

    **Time-boxed Crunches**

    * Fixed start and end dates
    * Payout at the end of the competition
    * Ideal for research problems, Kaggle-style challenges, or academic studies

    The Condor Game example in the starter kit demonstrates a continuous Crunch. See
    [Crunch Node Example](/getting-started/crunch-node-example) for details.
  </Accordion>

  <Accordion title="What happens after a time-boxed competition ends?">
    Coordinators retain access to:

    * All model outputs generated during the Crunch
    * Rankings, metrics, and aggregated performance reports
    * Coordinator dashboards for post-competition analysis

    If you want ongoing predictions after the initial Crunch ends, you can:

    * Switch to a continuous Crunch
    * Launch a new season
    * Integrate predictions via the Report Service API

    See [Crunch lifecycle](/core-concepts/crunch-lifecycle) for details on the end-of-competition flow.
  </Accordion>

  <Accordion title="What data does a Coordinator need to provide?">
    It depends on your use case:

    **Public market data** (e.g., crypto, equities, FX)

    * Your Crunch Node fetches data from public APIs or supported feeds
    * You define the format and delivery schedule in your predict service
    * Crunchers receive data through the model interface you define

    **Custom or proprietary data**

    * You provide historical datasets for training and test data for local development
    * You define features, targets, and evaluation rules in your public repository
    * For sensitive data, the protocol supports privacy-preserving techniques including TEE and MPC
      (see [Data security](/core-concepts/data-security-and-model-protection))
  </Accordion>

  <Accordion title="Who funds the prize pool?">
    Coordinators provide the prize pool, paid out in USDC. The protocol also supports CRNCH token
    emissions as an additional reward mechanism.

    Funds are deposited into a smart-contract escrow before the competition starts. The Coordinator
    runs checkpoints to distribute rewards, and participants claim their prizes through the
    [Tournament Hub](https://hub.crunchdao.com/).

    See [Crunch lifecycle](/core-concepts/crunch-lifecycle) for the full funding and payout flow.
  </Accordion>

  <Accordion title="What infrastructure does Crunch Labs provide?">
    Crunch Labs provides:

    * **Model Nodes** — Managed infrastructure for running participant models securely
    * **Model Orchestrator** — Deployment, scaling, and lifecycle management of model containers
    * **Tournament Hub** — Web platform where Crunchers discover and join competitions
    * **Crunch Protocol** — On-chain smart contracts for registration, checkpoints, and payouts
    * **Privacy tools** — TEE and MPC support for sensitive data (see [Data security](/core-concepts/data-security-and-model-protection))
    * **Starter kit** — Complete local environment with scoring, reporting, and model orchestration

    Coordinators are responsible for hosting their Crunch Node and providing the data and
    scoring logic. See [Crunch Nodes](/core-concepts/crunch-nodes) for details.
  </Accordion>

  <Accordion title="How much does it cost to run a Crunch?">
    Your main costs are:

    * **Prize pool** — The USDC you deposit for participant rewards
    * **Hosting** — A server for your Crunch Node (a simple cloud instance is usually sufficient)
    * **SOL** — Small transaction fees on Solana (less than 0.1 SOL for most operations)

    You do not pay for model execution infrastructure — that is managed by Crunch Labs through the
    Model Nodes.
  </Accordion>

  <Accordion title="Can I test before going to mainnet?">
    Yes. The recommended flow is:

    1. **Local** — Run the full stack on your machine with `make deploy`
    2. **Testnet** — Deploy to Solana devnet for end-to-end testing with real model submissions
    3. **Mainnet** — Go live once you have validated the full loop

    See [Testnet deployment](/getting-started/testnet-deployment) and
    [Mainnet deployment](/getting-started/mainnet-deployment).
  </Accordion>
</AccordionGroup>