Token-based thresholds excel at providing a clear, capital-aligned barrier to entry. A user must stake or hold a specific amount of the protocol's native token (e.g., 0.1% of total supply) to submit a proposal. This creates a direct financial stake in governance outcomes, as seen in Compound, where proposals require 65,000 COMP (~$2.6M at ATH). This model is simple to implement and leverages existing token distribution, but it inherently favors large holders (whales) and can lead to voter apathy among smaller token holders.
LABS
Comparisons
Proposal Thresholds: Token-based vs Reputation-based
A technical analysis comparing the two dominant models for setting governance proposal thresholds. We evaluate token-based systems, like those used by Uniswap and Arbitrum, against reputation-based systems, exemplified by Optimism's Citizen House, focusing on security, accessibility, and long-term protocol health.
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introduction
THE ANALYSIS
Introduction: The Gatekeepers of Governance
A data-driven comparison of token-based and reputation-based proposal thresholds, the foundational mechanisms that determine who can initiate change in a decentralized protocol.
Reputation-based thresholds take a different approach by decoupling proposal power from pure capital. A user's ability to propose is earned through verifiable contributions to the ecosystem, such as consistent participation, successful past proposals, or development work. Optimism's Citizen House uses a non-transferable Citizen NFT to grant proposal rights, aiming to prioritize engaged, knowledgeable community members over transient capital. This results in a trade-off: while it mitigates whale dominance, it introduces complexity in objectively measuring and assigning reputation, potentially creating a new centralized gatekeeper class.
The key trade-off: If your priority is sybil-resistance and capital efficiency for a protocol where financial alignment is paramount, choose a token-based system. If you prioritize meritocratic participation and long-term contributor alignment for a community-driven project, choose a reputation-based model. The choice fundamentally shapes whether your protocol is governed by its bank account or its most active citizens.
tldr-summary
Token-based vs Reputation-based
TL;DR: Core Differentiators
Key strengths and trade-offs for governance proposal thresholds at a glance.
01
Token-based: Capital Efficiency & Sybil Resistance
Direct capital alignment: A user's voting power is directly proportional to their financial stake (e.g., 1 token = 1 vote). This creates strong Sybil resistance, as acquiring influence requires real capital. This matters for DeFi protocols like Uniswap or Aave, where financial skin-in-the-game is critical for high-value treasury and parameter decisions.
02
Token-based: Clear Liquidity & Exit
Liquid and transferable influence: Governance rights are embedded in a liquid asset, allowing for easy entry/exit and price discovery on markets. This matters for protocols seeking broad, permissionless participation and where governance tokens have secondary utility (e.g., staking in Curve's gauge system).
03
Reputation-based: Expertise & Long-term Alignment
Meritocratic influence: Voting power is earned through verifiable contributions (e.g., code commits, forum posts, successful proposals) and decays over time (e.g., Optimism's Citizen House). This matters for ecosystem funding DAOs like Gitcoin or protocol R&D, where rewarding sustained, quality contribution is more important than capital weight.
04
Reputation-based: Mitigates Plutocracy
Decouples wealth from power: Prevents whales from dominating governance on day one, fostering more decentralized and community-driven decision-making. This matters for public goods funding or social protocols (e.g., Lens Protocol), where the goal is to align with active users and builders, not just token holders.
HEAD-TO-HEAD COMPARISON
Feature Comparison: Token-based vs Reputation-based Thresholds
Direct comparison of governance models for proposal submission in DAOs and protocols.
| Metric / Feature | Token-based Threshold | Reputation-based Threshold |
|---|---|---|
Primary Governance Model | Plutocratic (Wealth = Power) | Meritocratic (Contribution = Power) |
Sybil Attack Resistance | High (Cost = Token Purchase) | Medium (Requires Identity/Proof-of-Personhood) |
Barrier to Entry for Proposers | Capital Requirement | Reputation/Contribution History |
Aligns Incentives With | Token Price/Financial Stake | Protocol Usage & Long-term Health |
Commonly Used By | Liquid DAOs (e.g., Uniswap, Compound) | Contributor DAOs & Guilds (e.g., Gitcoin, Developer DAOs) |
Vulnerable to | Whale Dominance & Vote Buying | Reputation Farming & Collusion |
Implementation Complexity | Low (Native Token Balance) | High (Requires Sybil-resistant Identity Layer) |
pros-cons-a
PROS AND CONS
Token-based vs. Reputation-based Thresholds
Key strengths and trade-offs for governance proposal thresholds at a glance.
01
Token-based: Clear Economic Alignment
Direct skin-in-the-game: A user must hold or stake the protocol's native token (e.g., UNI, COMP, AAVE) to create a proposal. This aligns voting power with financial stake, as seen in Uniswap's 0.25% (2.5M UNI) threshold. This matters for protocols where capital commitment should equal governance influence.
02
Token-based: Sybil-Resistant & Verifiable
On-chain proof of stake: Thresholds are enforced via smart contracts, making them transparent and difficult to game without significant capital. This matters for large DeFi protocols with billions in TVL, where proposal spam must be economically prohibitive.
03
Token-based: Concentrates Power
Risk of plutocracy: Governance becomes dominated by whales, VCs, and large staking pools. For example, in many DAOs, <1% of addresses meet the proposal threshold. This matters for communities prioritizing broad, equitable participation over pure capital efficiency.
04
Token-based: High Barrier to Entry
Excludes non-capital contributions: Experts, active community members, and early contributors without large token holdings are locked out of proposal creation. This matters for growing protocols needing diverse, non-financial input to guide development.
05
Reputation-based: Meritocratic Participation
Rewards contribution, not capital: Reputation (non-transferable tokens or scores) is earned through verifiable actions like code commits, governance participation, or community moderation, as modeled by SourceCred or Colony. This matters for developer-centric ecosystems like Optimism's RetroPGF where expertise drives decisions.
06
Reputation-based: Sybil-Vulnerable & Subjective
Difficult to quantify fairly: Reputation systems require off-chain attestation or complex algorithms, creating attack vectors for collusion and subjective scoring disputes. This matters for protocols requiring high security and objective, automated enforcement.
pros-cons-b
Token-based vs Reputation-based
Reputation-based Thresholds: Pros and Cons
Key strengths and trade-offs at a glance for governance proposal thresholds.
01
Token-based: Capital Efficiency
Direct Sybil Resistance: The cost to acquire voting power is tied to the token's market price, making large-scale manipulation expensive. This is critical for high-value DeFi protocols like Uniswap or Aave where governance controls billions in TVL.
- Clear On-Chain Metric: Proposal power is transparent and easily verifiable via token balances.
02
Token-based: Liquidity & Composability
Integrated with DeFi Stack: Governance tokens (e.g., UNI, COMP) are liquid assets that can be used in lending, staking, and as collateral. This creates natural alignment between protocol health and voter economic interest.
- Standard Tooling: Supported by all major Snapshot strategies and wallet providers, simplifying integration.
03
Reputation-based: Long-Term Alignment
Resists Mercenary Capital: Voting power is earned through sustained contribution (e.g., development, curation, moderation), not purchased. This favors builders and active community members, as seen in systems like SourceCred or Optimism's Citizen House.
- Mitigates Whale Dominance: Prevents a single entity from buying majority influence, promoting decentralized decision-making.
04
Reputation-based: Adaptive Participation
Dynamic Power Distribution: Reputation can decay or be slashed for malicious actions, creating a self-policing system. This is vital for content curation DAOs like Forefront or developer guilds.
- Context-Specific Metrics: Power can be based on non-financial contributions like GitHub commits or forum posts, aligning incentives with actual work.
05
Token-based: Risk of Plutocracy
Voting Power = Wealth: Can lead to governance capture by large token holders (whales) or funds, marginalizing smaller, knowledgeable contributors. This is a major critique of early DAOs like Maker.
- Short-Term Incentives: Token holders may vote for immediate token price pumps over long-term protocol health.
06
Reputation-based: Complexity & Subjectivity
Off-Chain Attribution Challenges: Quantifying and verifying "reputation" (e.g., code quality, helpfulness) often requires subjective off-chain evaluation, introducing centralization points in the attestation process.
- Low Liquidity & Portability: Reputation is not a tradeable asset, which can reduce initial participation incentives and complicate exit for contributors.
CHOOSE YOUR PRIORITY
Decision Framework: When to Choose Which Model
Token-based Thresholds for DAO Governance
Verdict: The default for most financial DAOs. Strengths: Directly aligns voting power with economic stake, creating clear Sybil resistance. This is critical for treasuries managing significant capital (e.g., Uniswap, Aave). The model is simple to implement with standards like OpenZeppelin's Governor and provides a transparent, on-chain metric for proposal legitimacy. Weaknesses: Can lead to plutocracy, where large token holders dominate. Low token distribution can stifle participation, requiring very low thresholds that may increase spam.
Reputation-based Thresholds for DAO Governance
Verdict: Ideal for contributor-led or impact-focused DAOs. Strengths: Decouples governance power from pure capital, rewarding long-term contributors and experts (e.g., SourceCred in MakerDAO's forum). Systems like Colony's reputation mining prevent flash loan attacks and promote meritocracy. Better for protocol upgrades and strategic direction where deep understanding is key. Weaknesses: More complex to implement and audit. Reputation scores are often off-chain or rely on oracles, introducing centralization and liveness risks. Less liquid than tokens, making exit less clear.
verdict
THE ANALYSIS
Verdict and Strategic Recommendation
A strategic breakdown of token-based and reputation-based governance, guiding CTOs toward the optimal model for their protocol's stage and goals.
Token-based thresholds excel at providing clear, Sybil-resistant economic alignment because they tie voting power directly to a staked financial asset. For example, protocols like Uniswap and Compound use this model, where a proposal might require 2.5M UNI or 65K COMP to submit, creating a high-cost barrier to spam. This model is battle-tested, integrates seamlessly with DeFi primitives, and is predictable for large token holders. Its primary strength is security and capital efficiency, making it ideal for managing multi-billion dollar treasuries where proposal quality is paramount.
Reputation-based thresholds take a different approach by decoupling governance rights from liquid capital, instead awarding voting power based on verifiable contributions or past participation. This results in a trade-off: it fosters long-term, meritocratic alignment but introduces complexity in measuring and assigning reputation scores. Systems like SourceCred (used by MetaGov) or Gitcoin's workstream-based governance demonstrate this, where proposal power is earned, not bought. The key challenge is designing a robust, attack-resistant reputation oracle that accurately reflects valuable contribution.
The key trade-off is between capital efficiency and contributor inclusivity. If your priority is securing a high-value protocol with clear, auditable governance and you have an established token, choose token-based thresholds. This is the standard for mature DeFi protocols. If you prioritize bootstrapping an active, expert community from scratch, minimizing whale dominance, or governing a non-financial protocol, choose reputation-based thresholds. This model is often seen in early-stage DAOs like Developer DAOs or public goods funding ecosystems.
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