Reputation Round 2

A brief history: Why reputation in Grape?

When we began discussing reputation in May 2022, we all had different ideas about what reputation is, how it could be used and how it could benefit Grape. Over the past several months, we’ve explored reputation as a collective through workshops, experiments with emissions, debates around subDAOs, etc.

In parallel, we’ve also witnessed an enormous rise, crash and recovery of the Solana ecosystem that made clear the benefits of reputation and how it can be applied at Grape. Near the end of 2022, consensus within the Grape community suggested that reputation’s primary and original objective is to ensure that governance is always retained by implicated and active community members.

In 3Q2023, we voted to implement ScientistJoe’s reputation model. While this model serves as a great vision for Grape, it’s unfeasible to implement as a v1. If we want to make progress on reputation, we’ll need to revive the topic through a step-by-step approach.

Breaking down reputation

We’ve seen that reputation has 2 sides: the basis on which it’s acquired and how it is used:

  1. Criteria for attributing reputation include all of the different activities and signals that are taken into account in order to attribute reputation.
  2. Utility concerns how reputation is used practically and its significance to how power, control and governance are distributed across the community.

The interpretation of criteria can be broken down even further into 2 types:

  1. A points-based system would attribute a number of points to each activity. If an activity has an additional factor such as volume, size, quantity, depth, etc. the attribution of points could vary as a function of those factors.
  2. A tiered system whereby a DAO member acquires a level of reputation when he or she satisfies a set of criteria. This way of using reputation could integrate well with discussions around DAO membership levels (e.g. Neanderthal, Ape, etc.)

Next steps

In order to move forward quickly, @pie @Sejal_Rekhan and I would like to suggest a manual, test-and-learn approach and base these iterations on what has been revealed in the previous workshops. Below is a list of the 6 most popular criteria to consider for reputation listed by order of signaled importance:

  1. Realms Governance
  2. Use of token emissions
  3. Completion of tasks
  4. Bringing funds into the DAO
  5. DAO Call attendance
  6. Consistency of $GRAPE Holdings

To bootstrap reputation and ensure that reputation represents actions and activity we value, I would suggest to begin with a single criteria, the top criteria: participation in governance. This original experiment with reputation will be tracked manually and off-chain. It will give members the opportunity to look up their own scores, see how they place and how they are impacted by reputation in theoretical scenarios like 2-token governance.

Concretely to make this work, I’d like to put forth 3 steps:

  1. Extracting historical governance data (6 months) so we have a common basis of actions that we can use to calculate or assign reputation.
  2. Running a workshop to settle on both preliminary point values for voting, creating proposals and passing proposals as well as tiers based on those same actions for Great Ape and Neanderthal.
  3. Backtesting the criteria in the workshop will give us a clearer idea of the implications of applying the selected system.
  4. Every 2 weeks, we’ll do real-time attributions of reputation so we can see how reputation impacts the DAO and its members as if we were actually using the system.

Every month, we can meet for a new workshop session in order to evaluate the outcomes, adjust the points attribution or tiers and/or include the next criteria. The idea here is to understand the dynamics of reputation before giving it utility. Ultimately, however, the initial utility we are striving for involves 2-token governance.


We should be aware that technical resources and bandwidth are limited and may involve paying developers in Grape or USDC.

Industrializing the system will take time especially as it increases in complexity with more criteria.

Voting to take the system on-chain will likely involve members being for and against depending on their satisfaction with the system. There will always be a debate.

Starting manually like the DAO has done with past token emissions makes sense to lower the technical debt associated with iterating on the system. We should, however, strive for automation as the system matures.


I’m coming back to this post with 2 updates:

  1. We finally have a model based on real data that anyone can copy and update in order to calculate reputation based on votes, created proposals and passed proposals.
  2. I originally thought it best to start with a workshop. I didn’t follow through, and I should’ve communicated on that. However, this gave us space to build the model so we can work on something concrete. There’s only 1 way to go now and that’s forward. I’ll post a poll in Discord for workshop dates.

The Model
You can find the spreadsheet here. Copy it and edit it please. Then follow along below.

General notes:

  • tabs marked in red are raw data (up to date until Feb 16 2023)
  • tabs marked in green are editable (model’s parameters)
  • tabs marked in blue are results based on model parameters

Descriptions of each tab:

  1. proposals and votes - 2 tabs with raw data exported from Realms for the period
  2. points setup - assign points to the three actions (voted, created proposal and passed proposal)
  3. points per month - the number of new points per user per month
  4. cumulative points - the accrued number of points per user per month
  5. points rank - the rank of each user relative to all other users each month
  6. tier setup - design up to 3 membership tiers based on voting frequency (voted in x months of last n months), create proposal frequency (created proposal in x months of last n months) and passed proposal frequency (passed proposal in x months of last n months)
  7. tiers - the tier that each user falls into each month

Next steps:

  1. Run the workshop on how to use a model (poll on Discord during/after today’s DAO call)
  2. Let the models run with updated data for 1 month
  3. Members propose their models
  4. Vote and select the first model
  5. Test updated model by adding/modifying
  6. Rinse and repeat (2 - 5)

When we’re ready, we put it on chain.

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