  Mechanisms for decentralized finance on blockchains suffer from various
problems, including suboptimal price execution for users, latency, and a worse
user experience compared to their centralized counterparts. Recently, off-chain
marketplaces, colloquially called `intent markets,' have been proposed as a
solution to these problems. In these markets, agents called \emph{solvers}
compete to satisfy user orders, which may include complicated user-specified
conditions. We provide two formal models of solvers' strategic behavior: one
probabilistic and another deterministic. In our first model, solvers initially
pay upfront costs to enter a Dutch auction to fill the user's order and then
exert congestive, costly effort to search for prices for the user. Our results
show that the costs incurred by solvers result in restricted entry in the
market. Further, in the presence of costly effort and congestion, our results
counter-intuitively show that a planner who aims to maximize user welfare may
actually prefer to restrict entry, resulting in limited oligopoly. We then
introduce an alternative, optimization-based deterministic model which
corroborates these results. We conclude with extensions of our model to other
auctions within blockchains and non-cryptocurrency applications, such as the US
SEC's Proposal 615.
