Research & Reports

A Neutral Verifier for DeFi-Execution Agents

If you are building an agent that trades on-chain, how do you score whether it executed well? The quote is the obvious signal and the wrong one — a quote is a promise, and the realized fill is a different number. ClearTrace already runs a verifier for that gap: it fork-simulates a proposed route against live chain state and decomposes what the trade actually lost to fees, MEV, and slippage, scored the same way for every venue against a neutral baseline. This note describes the mechanism, shows a worked example on real data, and asks what a verifier like this would need to be to pull into an agent loop.

What it covers:

• The step function (propose calldata → realized fill) and the rubric that decomposes the quote-vs-fill gap into fee, MEV, and slippage in basis points.
• The rated-cell trust gate (≥30 realized samples, ≥7-day span) that keeps a burst of correlated samples from masquerading as an eval signal.
• Three ways it plugs into agent work — offline benchmark, online RL reward, and neutral referee — plus the honest limits (Ethereum-only, ~27 days, RFQ venues unrealized).

The Quote You Are Shown vs. the Price You Get

Every aggregator shows you a quote before you sign. ClearTrace's quote sampler captures that quote and fork-simulates the fill, so the gap between promise and delivery is measurable rather than assumed. Only cells rated at 30+ realized samples over a 7+ day span are claimed. This window, that gap is near zero for almost every venue, with one clear exception.

Key findings (Ethereum, rated quote-sampler cells):

• Seven of eight rated cells quote within about 2 bps of their realized fill: 1inch, Bebop, SushiSwap and the direct-Uniswap baseline at 0.0 bps, Odos at 0.21, ParaSwap at 1.0, KyberSwap at 2.02. Median across the rated aggregators: 0.21 bps. For the sampled book, the quote most aggregators display is a reliable predictor of the fill.
• OpenOcean is the outlier: its median realized fill ran 11.3 bps below the price it quoted, drawn from 1,154 realized samples (99% of its sampled quotes realized, so this is not a thin-sample artifact). That is roughly 5.6× the next-widest rated gap and the only double-digit gap in the set.
• Quote accuracy is a separate axis from execution cost. SushiSwap quotes almost perfectly (0.0 bps gap) yet posts the widest realized on-chain slippage in the rated set at 25.86 bps: an honest quote for an expensive fill. 1inch is tight on both (0.0 bps gap, 5.49 bps slippage, inside the 10.75 bps direct-Uniswap baseline). OpenOcean is wide on both.
• Honest bound: these are fork-simulated forward captures on a fixed set of pairs and sizes, not a census of every trade. The claim is that on the sampled book, OpenOcean's realized fills sat measurably below its quotes while its peers' did not.

Want to explore the same sampler data yourself? The interactive execution-quality explainer lets you isolate any aggregator across four trade sizes.

What Execution Quality Actually Costs You (Interactive)

The quote a DEX aggregator shows you is not what you get. We requested the identical trade from seven aggregators and replayed each against a mainnet fork to see what actually fills. The cheapest quotes were often the least reliable, reliability can degrade sharply with order size, and the one that almost never fails charges roughly 50x the rest. Explore reliability and realized cost across four trade sizes.

The Tightest Fill On-Chain Is a PMM, Not an AMM

Aggregate execution tables reward size: the venues with the most trades set the mental baseline, and a deep constant-product pool gets treated as about as tight as on-chain execution gets. Ranking sampled venues by realized slippage instead of by volume flips that. The tightest fill in the dataset is not the largest AMM or any aggregator. It is a proactive market maker (PMM).

Key findings (all chains, on-chain execution data):

• DODO posts the tightest median on-chain slippage of any venue sampled: 1.37 bps across 8,423 trades, roughly 8.3× inside the direct-Uniswap baseline (11.43 bps, 1,283,914 trades).
• It is tighter than every aggregator in the set; the best-executing aggregators this window are Bitget's DEX aggregator (4.79 bps) and 1inch (5.73 bps), both several basis points wider.
• The three tightest venues are all non-constant-product designs: DODO (1.37 bps) and woofi (2.67 bps) are PMMs, fluid (3.68 bps) is CLOB/smart-debt adjacent. A PMM prices from professional market makers around an external reference rather than walking a fixed curve, which collapses slippage on liquid pairs. Execution quality tracks routing topology.
• Honest bound: DODO's figure comes from a much smaller book (8,423 trades vs. Uniswap's 1.28M), so it reflects the pairs and sizes it actually served this window, not Uniswap's breadth. The claim is that the tightest fills are structural, not that a PMM beats an AMM on every pair.

RFQ at Size: One Aggregator Routes 86% of $1M Flow Off-Chain

The standing objection to off-chain RFQ routing is quote fade: a market maker shows a firm-looking price and delivers something worse by the time the fill lands, and the bigger the trade, the bigger the temptation. ClearTrace's quote sampler now has enough rated data on Ethereum to put a number on that fear, because exactly one sampled aggregator actually leans on RFQ at size.

Key findings (Ethereum, rated quote-sampler cells + on-chain data):

• At $1M trade size, KyberSwap routes 86.3% of sampled flow through off-chain RFQ makers (214 of 248 samples). Every other sampled aggregator (1inch, Bebop, Odos, ParaSwap, OpenOcean, Sushi, and the direct-Uniswap baseline) shows 0% RFQ share at that size. Across all sizes, its RFQ share is 20.6%.
• Quote accuracy does not degrade with size. The $1M tier realizes within 1.12 bps of quote (186 rated samples), tighter than the mostly-AMM $10k and $100k tiers (4.60 and 8.31 bps), precisely where routing flips to RFQ.
• Isolating the RFQ-routed $1M fills, the median gap is 2.69 bps (155 samples) versus roughly 0 bps for the thin AMM remainder (31 samples, indicative only). Committing 86% of $1M flow to off-chain makers costs a couple of basis points of quote fidelity, not the tens of basis points the quote-fade objection imagines. KyberSwap's overall rated gap is 2.61 bps.
• A fork simulation cannot replay an off-chain RFQ commitment, so the citable reliability measure is on-chain: KyberSwap's revert rate is 2.66%, below the direct-Uniswap baseline's 3.83%. The RFQ-heavy routing is not showing up as failed fills.

Update (2026-07-14): This report is withdrawn. Its RFQ-routing shares are a detection artifact — ClearTrace's quote sampler only parsed the RFQ flag from KyberSwap's API format, so KyberSwap read ~86% while every other aggregator (including heavy RFQ users like 1inch and 0x) read exactly 0.0%. A metric where most venues are exactly zero is unmeasured, not zero, so the RFQ metric has been removed from all published ClearTrace surfaces. See the methodology page.

The Uniswap Default: What Aggregators Are Actually Beating

ClearTrace's leaderboard flags one row as a baseline: Uniswap, traded directly, no aggregator in the path. That gives a clean yardstick for the question aggregators exist to answer — does routing through one actually beat just swapping on Uniswap?

Key findings (Ethereum, on-chain execution data):

• Direct Uniswap swaps cost a median 10.75 bps against the 1-minute VWAP (278,010 trades, 3.83% revert rate) — the bar every aggregator below is measured against.
• Only two of eight sampled aggregators beat that baseline on execution cost: 1inch (5.49 bps) and Bebop (9.30 bps, on a thinner 1,259-trade sample).
• Odos ties the baseline on cost (10.42 bps); its 17.41% headline revert rate is a documented bot-spam residual — address-rotating spam the v5 sender filter cannot fully separate dominates that cell, and the revert rate genuine Odos users experience is ≈0.2% (see the methodology page). CoW Protocol has the lowest revert rate in the sample (0.04%) but higher execution cost (15.19 bps) — cost and reliability don't move together.
• KyberSwap routes 87.2% of simulated $1M flow through off-chain RFQ desks (vs. 20.5% averaged across all sampled sizes), yet holds a below-baseline 2.66% revert rate — its heavy RFQ routing at size doesn't appear to cost it reliability.

Update (2026-07-14): The off-chain-RFQ-routing figure above is withdrawn. ClearTrace's sampler only parsed the RFQ flag from KyberSwap's quote format, so KyberSwap read high while every other venue read exactly 0.0% — a detection artifact, not a measurement. The RFQ metric has been removed from all published ClearTrace surfaces; this report's other findings are unaffected. See the methodology page.

DEX Aggregator Execution Scorecard — Edition 1 (July 2026)

The first rated edition of ClearTrace's recurring execution scorecard: five aggregators with rated quote-accuracy cells joined to on-chain execution, revert, and RFQ-routing data — frozen, dated, and SHA-256-hashed so the record can't be back-dated. The neutral, citeable alternative to self-reported "best price" and reliability claims.

Edition 1 findings (Ethereum, frozen July 4, 2026):

• Odos posts a rated 0.0 bps median quote gap — and a 23.78% on-chain revert rate (~1 in 4 routing transactions fails, 14.8× the direct-Uniswap baseline). Quote accuracy does not imply reliability.
• KyberSwap routes 86% of sampled $1M flow via off-chain RFQ desks, yet posts the widest rated quote gap (2.87 bps).
• Only three aggregators beat the direct-Uniswap execution baseline (10.54 bps): Bitget DEX (2.32), 1inch (7.02), and Bebop (9.73).

Update (2026-07-05): A post-publication audit found the Odos revert figure is dominated by address-rotating solver bots, not failing user transactions (genuine user rate ≈0.2%). The Edition 1 record stays frozen per its integrity model and carries a dated note; Edition 2 will use revert methodology v5. The other findings are unaffected. See the methodology page.

Update (2026-07-14): The RFQ-routing finding above is withdrawn. Its per-venue RFQ share was a detection artifact — the sampler only parsed the RFQ flag from KyberSwap's format, so every other venue read exactly 0.0%. Edition 1's frozen snapshot stays unchanged per its integrity model; Edition 2 carries the dated correction and drops the RFQ column. See the methodology page.

Quote Accuracy Results: Near-Perfect Quotes, Mixed Execution

One week after launching ClearTrace's fork-simulation quote sampler, the first rated cells are in: 3,557 realized samples across six aggregators over seven calendar days. Quote accuracy is higher than expected — five of the six rated aggregators deliver near-perfect quotes. The more important finding is what that accuracy doesn't predict.

Key findings (Ethereum, rated quote sampler cells + on-chain data):

• Most rated aggregators post ≤1 bps median quote gap: 1inch at 0.0 bps (598 samples), Odos at 0.03 bps (528 samples), ParaSwap at 1.0 bps (623 samples). Most aggregators quote almost exactly what they fill.
• KyberSwap is the outlier: 3.78 bps quote gap — widest among rated aggregators — despite routing 88.5% of $1M flow via off-chain RFQ desks (Hashflow / Native RFQ).
• The sharpest paradox: Odos posts 0.03 bps quote accuracy (528 rated samples) but a 19.86% on-chain revert rate — roughly 1 in 5 transactions fails before filling. Quote accuracy and execution reliability are separate dimensions.
• Among rated aggregators, only 1inch beats the direct-Uniswap execution baseline on cost (7.02 bps vs. 10.54 bps baseline) while also holding 0.0 bps quote accuracy and a 2.62% revert rate.

Update (2026-07-05): A sender-concentration audit found the Odos revert figure above was dominated by address-rotating solver bots, not user transactions failing — the rate experienced by genuine users is ≈0.2%. Revert methodology moved to v5 (stronger sender-level bot filter) on 2026-07-05; see the methodology page. The quote-accuracy findings are unaffected.

Update (2026-07-14): The off-chain-RFQ-routing figure above is withdrawn. ClearTrace's sampler only parsed the RFQ flag from KyberSwap's quote format, so KyberSwap read high while every other venue read exactly 0.0% — a detection artifact, not a measurement. The RFQ metric has been removed from all published ClearTrace surfaces; the quote-accuracy findings are unaffected. See the methodology page.

Aggregator Execution Quality: Why Lowest Revert Rate ≠ Best Outcome

A common shortcut for evaluating DEX aggregators is to compare revert rates — lower is safer. The on-chain data tells a more complicated story: the aggregators with the best revert rates post the worst execution costs, and vice versa. Using ClearTrace's latest Ethereum data and our newly launched quote-accuracy sampler, we map the full trade-off landscape across 14 aggregators.

Key findings (Ethereum, on-chain data):

• Tokenlon posts the lowest revert rate of any aggregator in our sample (0.07%, 2,339 trades) — yet its median execution cost is 64.48 bps vs. a 1-minute VWAP, more than 6× the direct-Uniswap baseline.
• Only two aggregators beat swapping on Uniswap directly (10.54 bps baseline): Bitget DEX at 2.32 bps and 1inch at 7.02 bps — both at the cost of higher revert rates.
• Odos and OpenOcean show revert rates of 19.86% and 11.69% respectively — roughly 1 in 5 or 1 in 9 transactions fails before filling.
• At $1M order size, KyberSwap routes 93.8% of flow through off-chain RFQ desks (Hashflow / Native RFQ), compared to 0% for 1inch, Odos, and ParaSwap — a routing topology shift that aggregate statistics miss.
• Quote accuracy (quoted vs. realized) is accumulating via our new fork-simulation sampler; no cells are rated yet. First rated results expected around June 30.

Update (2026-07-05): The Odos (19.86%) and OpenOcean (11.69%) figures above were computed under revert methodology v4 and are dominated by solver-bot spam, not failing user transactions — a sender-concentration audit puts genuine user revert rates near 0.2–0.4% for both. Methodology v5 (2026-07-05) filters these senders; the trade-off thesis of this report stands, but those two headline rates should not be cited. See the methodology page.

Update (2026-07-14): The off-chain-RFQ-routing figure above is withdrawn. ClearTrace's sampler only parsed the RFQ flag from KyberSwap's quote format, so KyberSwap read high while every other venue read exactly 0.0% — a detection artifact, not a measurement. The RFQ metric has been removed from all published ClearTrace surfaces; this report's trade-off thesis is unaffected. See the methodology page.

DEX Aggregator Execution Quality Benchmark — June 2026

Cross-frontend comparison of execution across major DEXs and aggregators on Ethereum, Base, Arbitrum, and Optimism. We measure realized slippage versus a 1-minute VWAP baseline and transaction revert rates directly from on-chain trace data — reported as separate metrics, not a single blended score.

Findings from the latest sync (figures are live on the dashboard):

• Revert rates vary widely by aggregator — CoW Protocol records the lowest (~0.1%), versus KyberSwap (~3.8%) and OpenOcean (~11.7%).
• On slippage, 1inch shows among the tightest median execution of the major aggregators (~7.5 bps), versus KyberSwap (~13 bps) and CoW Protocol (~15 bps).
• Lowest revert and lowest slippage aren't the same protocol — execution quality is multi-dimensional, which is why we publish each metric separately.
• Roughly half of analyzed routing volume traces to identified frontends; the remainder flows through unattributed proxy contracts we are actively resolving.

Cross-Frontend Attribution: Uncovering Hidden DEX Volume

Technical deep-dive into ClearTrace's 4-vector attribution engine: calldata suffix trapping, proxy-router hunting, multi-hop origin tracing, and fee-recipient attribution. Learn how we identify hidden mobile apps, institutional smart wallets, and anonymous frontends that traditional analytics miss.

Techniques Covered:

• Parsing raw calldata for hidden hex fingerprints
• Detecting proxy contracts via tx_to mismatches
• Window functions for behavioral sequence analysis
• Fee-recipient clustering for anonymous interface attribution