Inspired by the work done by Flashbots and L2Beat.
The goal of this open dashboard (see Contributing) is to facilitate open discussion and publish research grounded in real world data to accelerate development of protocols that solve UX, capital efficiency and execution quality issues.
We take a credibly neutral unopinionated stance and present information based upon deep research and on-chain data to help our community draw their own conclusions.
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Volume
$4.3B
6
1.004
-18 sec(s)
26.502 sec(s)
12.722 hour(s)
Supported chains
Intent-centric protocols like utilise a variety of auction mechanisms designed to optimise order execution either in terms of execution quality or speed. By matching buyers and sellers directly without the need for an intermediary liquidity pool the protocols can reduce the impact of front-running and slippage. The design of the auction is crucial because it creates different incentives for Fillers as well as different trade-offs depending on the exact mechanisms used. Commonly used auctions like FCFS are easy for protocols to run and result in fast order execution, however the lack the RFQ-like bid auction window that would allow multiple Fillers to compete with each other on execution quality.
The first accepted solver bid automatically wins the auction irrespective of whether another bid comes in at roughly the same time with a better price or outcome for the user
The openness of an auction is important in ensuring the trustworthiness of the result and proving there is no collusion between the protocol and Fillers. Open auctions allow all participants to see the auction process in real-time and verify the outcome. This transparency ensures that all bids are considered fairly, the auction rules are followed and the winning bid is the result of a fair and competitive process.
Protocol fillers rely on a webhook to recieve order flow data as of now. This enables the protocol to send orderflow data to selected fillers before other fillers which gives them a better chance at winning the FCFS auction
Intent centric protocols rely on Fillers to facilitate the execution of orders on their platform. One measure of the health of an Intent centric protocol is the number of Fillers that regularly fill orders and the extent to which these Fillers compete with each other to provide the best possible execution quality for user orders. Having a small number (or even one) of Fillers is a significant risk factor to the protocol.
Whilst most protocols are open and encourage free permissionless participation by any entity wishing to contribute bids for orderflow, some may require Fillers to apply and be whitelisted before they can access orderflow. Having a permissioned system increases risks of centralisation and heightens the risk of Censorship and amplifies the consequences of Filler Failure since it is not straight forward to for a new entity step in to provide bids for 'stuck' orders should no Fillers be available.
DLN allows any participant to perform Filling actions and provides comprehensive code (https://github.com/debridge-finance/dln-taker) to get Fillers up and running quickly.
Fillers often run sophisticated selection criteria to determine what orders they will fill and under what circumstances. Fillers additionally need to own sufficient inventory of the tokens on the appropriate chain to be able to execute an order they are bidding imposing limits on the competitiveness of filling entities based on their treasure and inventory management practices. As a result the range of orders that are filled differ between Fillers and can cause uncontested orders based on a number of factors including order value. It is not uncommon to see a tail off in Filler competition towards the higher value range.
More than one order value range is only filled by a single Filler. This represents an increased risk of monopolistic filling and will likely result in execution quality suffering and the user receiving a worse price than they might have otherwise.
The distribution of tokens filled by each Filler, based on the USD value of orders. It provides insights into which tokens are most frequently provided by different Fillers and highlights any specialization or concentration in specific tokens. A diverse range of tokens across Fillers indicates a healthy ecosystem, while a high concentration in particular tokens or Fillers may suggest potential liquidity or centralization risks.
Competition between fillers is a crucial element in the intent centric architecture design. Monopolistic filling discourages Fillers from increasing their bids to win order flow from other Fillers and results in reduced execution quality for the user. Another key metric of the health of an Intent based protocol is the degree of competition between Fillers to win order flow. Healthy ecosystems are demonstrated by the presence of multiple Fillers consistently submitting different competing bids for the same orders.
This protocol either has a single Filler or a single Filler is filling ≥ 90% of orders uncontested. This demonstrates very low competitiveness and will likely result in worse execution quality for user orders.
The distribution of order sizes gives insights into how users place orders and the extent to which they trust the protocol. Low trust or protocol airdrop farming activity is often represented by a heavy skew in orders towards the lower value end of the scale, whereas a more organic distribution between order values both demonstrates increased trust and organic behaviour.
XAxis - Value Buckets in USD
YAxis - Number of Orders
Wide ranging distribution of order values showing consistent protocol usage and a high degree of trust from users with larger value orders also seen consistently
How fast a protocol can satisfy an order is seemingly the main differentiator between protocols seeking to win order. The consistency of these order execution times per protocol give some insight into the ability of protocol Fillers to consistently service orders whilst performing inventory rebalancing operations themselves. As such, whilst optimising for speed on it's own doesn't lead to better execution quality (in fact it in some cases ends up with the opposite result), the consistency of execution from the protocol Fillers is an indicator of protocol health. Note that there can be some margin of error in this measurement based on the timing resolution of the block time headers for each chain.
| Fastest Execution Time | -18 sec(s) |
| Average Execution Time | 26.502 sec(s) |
| Slowest Execution Time | 12.722 hour(s) |
Some orders take multiple minutes to be filled resulting in the same or worse execution time compared to non-intent based protocols.
The consistency of these order execution times based on the order value gives some insight into the ability of protocol Fillers to consistently service orders whilst performing inventory rebalancing operations themselves. It's not uncommon to see execution speeds become significantly longer as the order sizes increase as fewer Fillers have inventory (and inventory deployed in the right places) to capitalise on the orderflow and bid to execute.
XAxis - Value Buckets in USD
YAxis - Execution time in seconds normalised using log(abs(time) + 2) * (time / abs(time))
Some orders take multiple minutes to be filled resulting in the same or worse execution time compared to non-intent based protocols.
Order execution times across source and destination chains provides some insight into the ability of protocol Fillers to consistently service orders whilst performing inventory rebalancing operations themselves along with exposing chain preferences. Chain block times and rebalancing frictions often skew Fillers to prioritise some chains over others when filling orders and this can lean to localised minimums and maximums in order execution time.
XAxis - Source Chain
YAxis - Speed by destination chain
When interacting with entirely blockchain resident programs (i.e. smart contracts) all transaction originating addresses have theoretically equal opportunity to obtain service (gas fees and block building stages notwithstanding). Intent based protocols incur additional practical complexities and, coupled with a lack of standarisation between how intents are expressed, auctions are run and how Fillers obtain information about orders to fill, results in additional layers of infrastructure needing to be created. Largely, these additional layers are not implemented fully on chain and / or rely on messaging passing mechanisms which can further widen the ways that participation can be limited. Performing some of the calculation, matching or execution logic off chain introduces a potential source of centralisation. Centralisation negates the guarantees of a decentralised system where if only a single participant is acting honestly and rationally, there is a level playing field for all. Depending on the design of an protocol, centralisation can occur through multiple mechanisms like off chain order advertising, order-bid matching, auction execution, cross-chain message passing, permissioned relayers or executors and others.
Protocol fillers rely on a webhook to recieve order flow data as of now. While this doesn't completely disable the fillers from filling the order as it can still be picked up from the mempool, most fillers will rely on the protocol run webhook which means the orders can be prevented from ever reaching any fillers.
Intent centric protocols require a Filler to submit a bid and execute transfers / actions that a user order specifies. Without at least one Filler facilitating orders, an Intent based protocol is unable to offer a service to users. Having no Fillers to facilitate an order (or all orders) is a existential risk factor for the protocol which is usually mitigated by the protocol running their own simplistic Filler to provide a minimum level of service. However, should there be no Fillers available to satisfy an order or, if all Fillers decline to service a particular order, there is the potential for an order to be trapped in-flight unless another Filler steps in or the facilitating protocol has an “escape hatch” mechanism for the order originator to cancel their order and have their funds returned.
Protocol fillers rely on a webhook to recieve order flow data as of now. While users can always fallback to looking for orderflow in the mempool if the webhook ever goes down, it does introduce a possiblity of downtime or atleast less efficient trades if the webhook ever goes down
The chart below shows the relationship between the fees earned by fillers and the gas paid by them. Gas fees often eat into margin. As these lines converge, intent based systems may or may not see a degradation in filler competition.
XAxis - Date
YAxis - USD
