Launching a Reputation-Weighted Governance Proposal System

Reputation-weighted governance is a mechanism designed to align long-term participation with decision-making power. Unlike token-based voting, where influence can be bought, a user's reputation score is typically earned through verifiable, on-chain contributions to the protocol—such as consistent participation, successful proposal execution, or providing liquidity. This score is non-transferable (soulbound) and can decay over time to ensure active engagement. Systems like Colony and early concepts from DAOstack pioneered this approach to combat voter apathy and plutocracy in decentralized organizations.

The core technical architecture involves three smart contract modules: a Reputation Registry, a Proposal Engine, and a Voting Module. The Reputation Registry is the source of truth, minting and tracking reputation based on predefined actions. The Proposal Engine handles the lifecycle of a proposal, from submission and sponsorship to execution. The Voting Module calculates voting power by querying the registry and tallies votes. A common pattern is to use a quadratic voting formula within the voting module, where power = sqrt(reputation), to further mitigate concentration of influence.

To launch, you first define the reputation minting rules. These are the specific, on-chain actions that grant reputation points. For a DeFi DAO, this could include: providing liquidity for >90 days, successfully passing a prior governance proposal, or consistently voting on proposals. These rules are encoded in a Minter contract that has permission to call mint on the Repistry. It's crucial that these rules are transparent and immutable post-launch to maintain system legitimacy. Use an initial bootstrap phase to seed reputation among founding contributors.

Here is a simplified code snippet for a basic Reputation Registry using OpenZeppelin's ERC20 as a base for the non-transferable token, often called a vToken or soulbound token. The key override is the _update function to block transfers.

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import "@openzeppelin/contracts/token/ERC20/ERC20.sol";

contract ReputationToken is ERC20 {
    address public governanceMinter;

    constructor(string memory name_, string memory symbol_) ERC20(name_, symbol_) {}

    function setMinter(address minter_) external {
        // Typically called once during setup
        governanceMinter = minter_;
    }

    function mint(address to, uint256 amount) external {
        require(msg.sender == governanceMinter, "Unauthorized");
        _mint(to, amount);
    }

    // Override to make token non-transferable (soulbound)
    function _update(address from, address to, uint256 value) internal virtual override {
        require(from == address(0) || to == address(0), "Reputation is non-transferable");
        super._update(from, to, value);
    }
}

Integrating this with a voting system requires the voting contract to read the reputation balance. A proposal passes based on a quorum (minimum total reputation voting) and a supermajority threshold (e.g., 60% of votes cast). You must also implement execution delays and timelocks for high-stakes decisions. For security, consider using a module pattern where the core reputation contract is upgradeable via a separate governance process, and the minter/voting contracts are separate, audited modules. Always conduct thorough testing on a testnet with simulated proposal cycles before mainnet deployment.

Key challenges include sybil resistance for initial reputation distribution, designing fair reputation decay (e.g., 2% per month) to ensure activity, and preventing proposal spam. Successful implementations often use a stake-weighted or conviction voting layer on top of reputation for funding proposals. The end goal is a system where governance power reflects proven, ongoing commitment, creating a more resilient and aligned decentralized organization. For further reading, review the Compound Governance system for inspiration on proposal mechanics and the SourceCred project for advanced reputation algorithms.

A reputation-weighted governance system requires a modular architecture. You will need a token contract for voting power, a staking mechanism to lock tokens and generate reputation, and a proposal contract to manage the governance lifecycle. For this tutorial, we'll use Solidity and the Foundry development framework, as it provides excellent testing and deployment tooling for EVM chains. Begin by initializing a new Foundry project with forge init reputation-governance and install OpenZeppelin Contracts for secure, audited base implementations using forge install OpenZeppelin/openzeppelin-contracts.

The core of the system is the reputation token, an ERC-20 with snapshot capabilities. Use OpenZeppelin's ERC20Snapshot contract to allow for historical voting power lookups, which are critical for proposals that reference a specific block. You must also implement a staking contract that accepts your governance token and mints a non-transferable reputation token (ERC-1155 or a custom ERC-20 with a block on transfers) in return. The amount of reputation minted can be a linear function of the staked amount and time, using a vesting schedule to prevent instant power accumulation.

Next, set up the proposal contract. This should inherit from a governance standard like OpenZeppelin's Governor contract. The key customization is overriding the _getVotes function to read voting power from your reputation token snapshot instead of a standard ERC-20 balance. Ensure your development environment is configured for your target chain (e.g., Ethereum Sepolia, Arbitrum Sepolia). Set up a .env file with your RPC URL (RPC_URL) and a private key for deployment (PRIVATE_KEY). Use forge script with the --broadcast flag to deploy your contracts in the correct order: Token, then Staking, then Governor.

Testing is crucial. Write comprehensive Foundry tests in Solidity to simulate the full governance flow: staking tokens to earn reputation, creating a proposal, voting with reputation power, and executing the proposal. Use the vm.roll() cheatcode to simulate the passage of time for proposal voting periods and staking locks. Test edge cases, such as voting with reputation earned after a proposal snapshot is taken (it should not count) and the ability to slash reputation for malicious behavior. Aim for 100% branch coverage on your core governance functions.

Finally, prepare for production deployment. Decide on governance parameters: proposal threshold, voting delay, voting period, and quorum. These are set in the governor constructor and are chain-specific. For mainnet deployments, consider using a proxy upgrade pattern (like UUPS) for your governor contract to allow for future improvements. Use a block explorer verifier like Sourcify or Etherscan to publish your contract source code, enhancing transparency and trust in your decentralized governance system.

A reputation-weighted governance system assigns voting power based on a user's non-transferable reputation score, which is earned through verifiable contributions to the protocol. This is a fundamental shift from token-weighted voting, where capital concentration can dominate decisions. Reputation is typically accrued through actions like submitting successful proposals, completing bounties, providing accurate data to oracles, or consistent participation in forums. This model, inspired by projects like Colony and early concepts from DAOstack, aims to align voting power with proven engagement and expertise rather than mere financial stake.

Quadratic Voting (QV) is a mechanism often layered on top of reputation to further enhance decision quality. In QV, the cost of casting votes increases quadratically with the number of votes allocated to a single option. For example, buying 1 vote might cost 1 credit, but buying 3 votes for the same proposal would cost 9 credits (3²). This creates a convex cost function that makes it exponentially expensive for any single entity to fully dominate a vote, encouraging voters to spread their influence across multiple proposals they care about. The pairing with reputation means users spend reputation-derived voting credits, not tokens.

Implementing this system requires a smart contract architecture with several key components. First, a Reputation Registry contract must mint and manage non-transferable reputation tokens (e.g., ERC-20 with transfers disabled or an ERC-1155 type). A separate Quadratic Voting Module handles the voting logic, calculating the cost as cost = votes² and checking against a user's balance of voting credits. A common practice is to allocate voting credits in a separate, spendable ERC-20 token that is minted based on a snapshot of the reputation registry at the start of each voting period.

Here is a simplified conceptual outline for a Quadratic Voting contract function:

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function castVote(uint256 proposalId, uint256 voteAmount) external {
    uint256 cost = voteAmount * voteAmount; // Quadratic cost
    uint256 userCredits = votingCredits.balanceOf(msg.sender);
    require(userCredits >= cost, "Insufficient voting credits");
    votingCredits.burn(msg.sender, cost);
    votes[proposalId][msg.sender] += voteAmount;
}

This ensures the cost is deducted correctly. The reputation system would separately govern the distribution of the votingCredits to users at the epoch's start.

Key design considerations include the sybil-resistance of your reputation source, the frequency of reputation issuance/decay (e.g., halving every year), and the UI complexity of explaining quadratic costs to users. Tools like Tally or Snapshot with custom strategies can be adapted for off-chain voting, while on-chain implementations require careful gas optimization. The goal is to create a more resilient and thoughtful governance process that rewards long-term, constructive participation over short-term capital allocation.

The foundation of a reputation-weighted governance system is a non-transferable NFT contract. Unlike standard ERC-721 tokens, these reputation tokens must be soulbound to prevent vote-buying and Sybil attacks. We'll use the OpenZeppelin library to build an ERC721 contract with a critical override: the _beforeTokenTransfer function must revert for all transfers except minting and burning. This ensures reputation is earned, not traded. The contract will store the reputation score as a uint256 value in the token's metadata, accessible via the tokenURI.

Each reputation NFT is minted to a user's address upon meeting predefined criteria, such as active protocol participation or successful proposal execution. The contract must include permissioned minting and burning functions, typically restricted to a governance module or an off-chain oracle. For example, a function like mintReputation(address to, uint256 score) would be callable only by the designated MINTER_ROLE. The score is often stored on-chain as a mapping: mapping(uint256 tokenId => uint256 score) public reputationScores. This allows the governance contract to query a user's voting power directly.

Consider gas optimization and upgradeability from the start. Storing scores in a uint256 array within the contract state is straightforward but can become expensive for frequent updates. An alternative is to store a score hash on-chain and verify scores via Merkle proofs, updating the Merkle root in batches. For future adjustments to the reputation algorithm, implement the contract using a proxy pattern (like UUPS) to separate logic from storage. This allows you to upgrade the scoring logic without losing existing token IDs and user data.

Here's a minimal code snippet for the core transfer restriction using OpenZeppelin's ERC721:

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import "@openzeppelin/contracts/token/ERC721/ERC721.sol";
contract ReputationNFT is ERC721 {
    function _beforeTokenTransfer(address from, address to, uint256 tokenId, uint256 batchSize) internal virtual override {
        require(from == address(0) || to == address(0), "ReputationNFT: non-transferable");
        super._beforeTokenTransfer(from, to, tokenId, batchSize);
    }
}

This ensures tokens can only be minted (from == address(0)) or burned (to == address(0)).

Finally, integrate with a decentralized identity standard like ERC-6551 (Token Bound Accounts) to allow each reputation NFT to own assets and interact with protocols autonomously. This transforms the NFT from a passive record into an active agent, enabling complex behaviors like automatic delegation of voting power or revenue sharing from owned assets. The completed contract serves as the single source of truth for reputation, feeding into the subsequent governance module that calculates vote weight.

The core of a reputation-weighted governance system is a custom Governor contract that queries a separate Reputation contract for voting power. Instead of using the standard getVotes function, which checks an ERC-20 token balance, you will override it to call your reputation module. This architectural separation is crucial: the Reputation contract becomes the single source of truth for a user's governance weight, which can be updated based on off-chain or on-chain actions without modifying the governor itself.

You must extend the Governor contract and override two key functions: getVotes and _getVotes. The public getVotes function is what external interfaces will call, while _getVotes is the internal function used during proposal state calculations. Both should return the value from your Reputation contract. Here is a basic Solidity implementation skeleton:

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import "@openzeppelin/contracts/governance/Governor.sol";

contract ReputationGovernor is Governor {
    IReputation public immutable reputationToken;

    constructor(IReputation _reputationToken) Governor("ReputationGovernor") {
        reputationToken = _reputationToken;
    }

    function getVotes(address account, uint256 blockNumber) public view override returns (uint256) {
        return reputationToken.getPastReputation(account, blockNumber);
    }

    function _getVotes(
        address account,
        uint256 blockNumber,
        bytes memory // params
    ) internal view override returns (uint256) {
        return getVotes(account, blockNumber);
    }
    // ... quorum, voting delay, and period functions
}

The IReputation interface must define a getPastReputation function that mirrors the getPastVotes pattern from ERC-20Votes. This is essential for snapshotting, as proposals record voting power at the block when the proposal is created. Your reputation contract must implement a mechanism to store historical reputation checkpoints. Without this, a user could increase their reputation after a proposal is made and gain extra voting power, breaking the snapshot security model.

Beyond voting power, you need to configure the governor's parameters. The votingDelay (blocks between proposal creation and voting start) and votingPeriod (duration of the voting phase) should be set considering your community's pace. More importantly, you must define a quorum function. In a token-based system, quorum is often a percentage of the total supply. For reputation, you might use a fixed number or a percentage of the total reputation ever minted, calculated via a function like reputationToken.totalPastReputation(blockNumber).

Finally, integrate this governor with a standard TimelockController for secure, delayed execution of successful proposals. The complete system flow is: 1) A proposal is submitted, locking snapshot weights. 2) Reputation holders vote during the votingPeriod. 3) If quorum and majority are met, the proposal is queued in the Timelock. 4) After the timelock delay, anyone can execute the proposal. This structure, using battle-tested OpenZeppelin components, provides a robust foundation for on-chain reputation governance.

A reputation-based proposal threshold ensures that the ability to initiate governance actions is proportional to a participant's proven contribution and alignment with the protocol. Instead of a static token requirement (e.g., 1% of total supply), the threshold is a function of a user's reputationScore. This prevents spam from new or low-reputation accounts while empowering long-term, high-value contributors. The threshold logic is typically enforced in the propose function of your governance contract, which checks if msg.sender meets the requirement before allowing a proposal to be created.

The implementation involves defining a mathematical relationship between reputation and the required threshold. A common model is a reverse linear scaling: as reputation increases, the required threshold decreases. For example, you might implement a formula where proposalThreshold = baseThreshold * (1 / (1 + reputationScore / scaleFactor)). Here, a baseThreshold of 1000 tokens and a scaleFactor of 100 would mean a user with a reputationScore of 0 needs the full 1000 tokens to propose, while a user with a score of 100 would need only 500 tokens.

Here is a simplified Solidity code snippet illustrating this check within a governance contract:

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function propose(address[] memory targets, uint256[] memory values, bytes[] memory calldatas, string memory description) public override returns (uint256) {
    IReputationRegistry repo = IReputationRegistry(reputationRegistryAddress);
    uint256 senderReputation = repo.getReputation(msg.sender);
    uint256 requiredTokens = calculateThreshold(senderReputation);

    require(token.balanceOf(msg.sender) >= requiredTokens, "Proposer token balance below reputation-based threshold");
    // ... rest of proposal creation logic
}

function calculateThreshold(uint256 reputationScore) public view returns (uint256) {
    uint256 base = 1000 * 1e18; // 1000 tokens with 18 decimals
    uint256 scale = 100;
    // Threshold = base / (1 + reputation/scale)
    return base * scale / (scale + reputationScore);
}

This function fetches the proposer's reputation, calculates their personalized token threshold, and validates their balance.

Key design considerations include setting appropriate baseThreshold and scaleFactor parameters. The baseThreshold should be high enough to deter casual spam but not so high it excludes meaningful community members. The scaleFactor controls how quickly the threshold decays with reputation; a lower factor means reputation reduces the requirement more aggressively. These parameters should be calibrated through governance simulations and may themselves be governed by future proposals. It's also crucial to ensure the reputationScore is sourced from a trusted and immutable ReputationRegistry to prevent manipulation.

Beyond the basic model, you can implement more sophisticated logic. Options include tiered thresholds (e.g., Bronze, Silver, Gold tiers with fixed requirements), quadratic scaling to further reduce barriers for highly reputable users, or multipliers for specific reputation traits (e.g., a bonus for consistent voting participation). The threshold calculation can also incorporate other factors like delegated voting power, allowing a user to meet the threshold with their own tokens plus tokens delegated to them for voting, further integrating with the broader governance system.

Finally, this mechanism must be transparent and verifiable. Users should be able to query a view function to check their current required proposal threshold based on their live reputation score. This fosters trust and allows contributors to understand exactly what is required to participate in shaping the protocol's future. Implementing this step successfully creates a dynamic, meritocratic gateway for proposal creation, aligning governance power with demonstrated commitment.

Quadratic voting (QV) is a governance mechanism where the cost of casting votes increases with the square of the number of votes. For example, to cast 1 vote costs 1 unit of voting power, but to cast 2 votes costs 4 units (2²), and 3 votes costs 9 units (3²). This non-linear scaling makes it economically prohibitive for a single large token holder (a 'whale') to dominate a proposal, as their influence grows linearly with their stake while their cost grows quadratically. This promotes more equitable outcomes by amplifying the voices of smaller, more numerous stakeholders.

To implement this, you need to modify the core voting logic. Instead of a simple 1 token = 1 vote tally, you must calculate the quadratic cost of a user's vote choice. A common approach is to have users 'spend' a governance token or a derived voting credit. The contract must validate that a user's balance is sufficient to cover the quadratic cost of their desired vote weight before recording it. The Gitcoin Grants rounds are a prominent real-world example of quadratic funding, which uses similar mathematical principles.

Here is a simplified Solidity function snippet demonstrating the core check:

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function _castQuadraticVote(address voter, uint256 voteWeight) internal {
    uint256 cost = voteWeight * voteWeight; // Quadratic cost calculation
    require(votingCreditBalance[voter] >= cost, "Insufficient voting credits");
    votingCreditBalance[voter] -= cost;
    votesForProposal += voteWeight; // Tally the linear vote weight
}

This function ensures a user pays the quadratic cost (voteWeight²) in credits to have their linear voteWeight counted. The state must track both the spent credits and the tallied votes separately.

Key design decisions include choosing the voting asset: a dedicated voting ERC-20 token, a non-transferable voting credit earned by staking, or a reputation score from an on-chain system. You must also decide if votes are commit-reveal (to prevent tactical voting) or public. Furthermore, consider implementing a minimum vote weight to prevent spam and a mechanism to return unspent credits after the voting period concludes. Each choice involves trade-offs between complexity, gas costs, and sybil resistance.

Finally, integrate this logic with your proposal lifecycle from Step 3. The voting period should trigger the QV mechanism, and the proposal outcome should be determined by the sum of the linearly tallied votes. Always conduct thorough testing with varying stake distributions to simulate whale and community scenarios. Use a framework like Foundry or Hardhat to write tests that verify the quadratic cost enforcement prevents a whale with 100 units from outweighing 10 users with 1 unit each, which is a primary goal of this system.

The system you've implemented uses a ReputationToken to quantify user contributions, a ReputationGovernor to process proposals with vote weight based on reputation, and a ReputationOracle to manage off-chain reputation data. This architecture separates the logic of reputation calculation from on-chain governance, allowing for flexible, upgradeable reputation models while keeping gas costs for voting predictable. Key security measures include using a timelock for executed proposals and ensuring only the oracle can update reputation scores to prevent manipulation.

For production deployment, several critical steps remain. First, thoroughly audit your custom ReputationOracle logic and the integration points with your data sources (e.g., Snapshot, custom APIs). Use a tool like Slither or MythX for automated analysis and consider a professional audit from firms like Trail of Bits or OpenZeppelin. Second, design a clear and transparent reputation formula. Document the exact metrics (e.g., token holdings, protocol usage, forum activity) and their weights so users understand how their voting power is derived.

Next, plan your governance lifecycle. Use a testnet deployment to run through full proposal cycles: 1) reputation snapshot, 2) proposal creation, 3) voting period with displayed weights, and 4) execution via timelock. Tools like Tenderly can help simulate and debug these flows. Establish off-chain processes for your community, including a forum (e.g., Commonwealth) for discussion and a front-end interface (using a library like Governor UI) that clearly displays a user's reputation score and voting power.

Consider the long-term evolution of your system. How will you handle reputation decay or inflation? You may need to add functions to the oracle for score adjustments. Explore advanced mechanisms like conviction voting or quadratic funding that can be layered on top of the reputation-weighted base. The OpenZeppelin Governor documentation is an excellent resource for further customization.

Finally, the success of any governance system depends on community participation. Educate your users on how reputation is earned and the impact of their vote. Start with lower-stakes proposals to build confidence in the process. By combining robust on-chain contracts with transparent off-chain processes, you create a legitimate and effective decentralized governance framework.