Announcing the new MKR.tools
A big focus of this new version was providing users a more in-depth look into individual CDPs (example CDP 3228 ). A few items of note:
After several months of development, I’m excited to finally release the new MKR.tools dashboard. This post will briefly highlight a few of the new features and layout future plans for the dashboard.
The historical bites section now includes a sortable table of every bite and the amount of peth liquidated. The amounts are also shown as bubble sizes in the chart:
The liquidations page now has labels for CDPs with over 1 million in Dai debt. Tooltips also show individual CDPs and how they factor into total liquidations amounts.
Another commonly requested feature throughout this year has been more statistics around the various tokens in the MakerDAO ecosystem. To start, a new Dai page has been added which shows:
- Dai transactions counts and volume charts and weekly statistics
- Dai velocity over time
The new MKR page shows current burner contract balances and a forecasted burn which takes into account the current accrued stability fees across all CDPs. An interactive calculator will be added soon to allow users to change system parameters and forecasted Dai growth for more accurate MKR valuation metrics.
More animations like this are in the works. My next attempt will be to visualize the movements of Dai and interactions between dApps in the DeFi stack.
Future plans for MKR.tools is shaped a lot by immediate needs of the community, but here’s a few things I’m exploring and would like to research more:
- Dai usage in individual DeFi dApps (0x, Augur, Uniswap, DyDx, Compound, Dharma, etc)
- Governance statistics tracking votes for system parameters and collateral types
- In depth analysis of potential collateral types
To expand on the last point, as multi-collateral Dai goes live and Dai sees incredible growth in the space, risk analysis of collateral types will become crucial to keeping the system healthy. Lots of general token metrics exist around transaction counts, DAU’s, etc, however I believe more specialized on-chain analysis of these unique systems is required. Along with MKR.tools style analytics of additional collateral types, I plan to look at:
- Liquidity (gauging what volume is faked, looking at order book depths and market microstructures)
- Gini coefficients (top holders, lockups)
- General statistics (correlations to other crypto-assets, price volatility, etc)
- Black swan risks (regulatory, hacks, etc)
As always, feel free to reach out on Twitter if you’re interested in collaborating on any research or have comments/questions/suggestions for the dashboard.