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SamTinnerholm

Nice paper, and thanks for releasing the dataset.

The "top-1% winners are patient limit-order liquidity providers, not insiders" finding is interesting, and I'd love to see it extended cross-venue.

I work on tooling that normalizes orderbooks across Polymarket, Kalshi, Limitless, and Smarkets. From that angle, a lot of what looks locally like skilled Polymarket market-making turns out to be cross-venue arbitrage that happens to land on Polymarket. The same underlying question routinely trades 3-8% apart across venues for hours at meaningful depth, and a fast multi-venue stack rests limits on the lagging book at the exact moments the leading book moves. Locally that's indistinguishable from disciplined liquidity provision; cross-venue it's closer to FX triangular arb on the consensus price.

If your timestamps are fine-grained enough, a clean follow-up: for the top 1% of Polymarket profit-takers, what fraction of fills land within N seconds of a same-question move on Kalshi or Limitless? If it's materially above baseline, some of "skill" resolves into "cross-venue infrastructure" — which is also a more durable edge than within-venue alpha, so it could partly explain the weak monthly persistence you observe (the cross-venue gap closes when too many players run the same stack).

This might also be consistent with your insider-trading conclusion rather than against it: an insider on a real-world event has every reason to hit the lowest-friction venue with aggressive market orders (Polymarket: permissionless wallets, no KYC, no withdrawal limits). That's a fundamentally different profile from the patient limit-posting strategy your top bucket runs, so the two populations cleanly separate in the data even if both are present.

Show HN: DomeAPI (YC F25) was acquired. pmxt is the open-source equivalent

https://github.com/pmxt-dev/pmxt

Hi HN, I'm the maintainer of pmxt.With Polymarket's recent acquisition of DomeAPI to bring their infrastructure in-house, there is a sudden gap for developers building cross-market arbitrage bots, tracking whale wallets, or running quantitative models across prediction markets. If you are trading across Polymarket, Kalshi, or Limitless, you need a unified API to avoid getting locked into a...

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We bootstrapped to 450 stars by giving away risk free arbitrage opportunities

I maintain pmxt.dev, an open-source unified API for prediction markets (Polymarket, Kalshi, etc.). We essentially built "ccxt for prediction markets."We’ve hit ~450 stars and 30k downloads. We are currently the standard in the space. Limitless.Exchange endorsed us, and the founder of ccxt has even starred the repo.What worked: Instead of traditional marketing, we focused on "Utility Marketing."...

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We just released websockets today.

Test coverage is high. I'd recommend checking it out to form your own opinions.

Show HN: Open-source library to unify Polymarket and Kalshi APIs

https://github.com/qoery-com/pmxt

I noticed prediction markets are becoming fragmented (Polymarket on-chain, Kalshi regulated/off-chain), making it painful to write cross-exchange bots. Crypto has ccxt to standardize exchange APIs, but nothing existed for prediction markets.I built pmxt to solve this. It normalizes the data across platforms so you can treat them as a single liquidity source.It’s open source and I'm looking for...

( Read More... | 1 comment | on HN )

Show HN: I built a Python wrapper to query Uniswap v3 directly

https://github.com/qoery-com/qoery-py

I'm a university student and needed DeFi data for my project. CoinGecko's API pricing was way out of my budget (like, not even close). $35+/month just for high-granularity data – and that's not even minute-by-minute! So I did what any broke student would do – I started querying the blockchain directly instead.Turns out, going straight to the source is not only cheaper, but I could offer the...

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Show HN: I built a crypto data API that ignores CEXs to cut costs by 85%

https://qoery.com/

The current pricing for crypto data APIs (CoinGecko/CMC) is based on a legacy requirement: maintaining hundreds of real-time websocket connections to centralized exchanges (Binance, Coinbase, Kraken, etc.).That infrastructure is heavy, expensive, and requires constant maintenance to filter wash-trading and normalize order books.But if you are building for DeFi, that data is technically...

( Read More... | no comments | 2 points | on HN )

Show HN: 85% Cheaper Crypto Data

https://qoery.com/

If you've ever tried to integrate crypto market data into an app, you know the pricing for commercial APIs gets crazy fast. I couldn't justify the cost for my projects, so I built my own solution.I learned to index and query the blockchain directly, cutting out the middleman fees.The result is qoery.com.

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Show HN: Mintlify Ignored This Feature Request for 6 Months. Here's My Solution

https://github.com/madrasly/madrasly

Mintlify users have been begging for pre-filled API playground fields for months. The GitHub discussion has people literally saying "I just lost two hours of my day banging my head against this issue." (https://github.com/orgs/mintlify/discussions/759) The problem? When you click "Try it" in Mintlify's playground, every field is empty, even though your OpenAPI spec has perfectly good example...

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Cool, but it's a bit hard to rotate. Could be more intuitive.
I tried creating a tool, it's been stuck "generating" for a few minutes now.
I can't seem to create tools on https://anytoolhq.com/dashboard. Report back when it works, and I'll give it a try.
Cool. Will try this with my agent.

Quick comment: the code on the website isn't using any sort of intellisense or highlighting

Hi Bob,

I see what you're saying. Stay laser-focused on potential enterprise customers, and iterate with them until they pay.

This is brilliant advice. I'll email my users to find out.
Some background: I previously built and sold a Chrome extension that reached 30k users, and created an open source tool with around 150 stars and 11k downloads that's been adopted by companies like Goldman Sachs.

I'm now building qoery.com. The product is functional but not fully polished. I have 60 sign-ups but no paying customers yet. The feedback I'm getting from existing users is "improve the product and we'll pay."

I've spent the last two weeks iterating heavily on the product based on this feedback. It's significantly better now, but growth has completely stagnated during this time.

So I'm facing a dilemma: should I keep iterating based on user feedback until I convert those first users to paid customers? Or should I shift focus to customer acquisition and try to find users who might pay for what exists today?

Looking for advice from founders who've been through this.

Re:Show HN: Erdos – open-source, AI data science IDE on Monday October 27, 2025 @01:28PM (#45723850)
I can't tell how this differs to Cursor from your website. How is it different?
Type 'EV adoption rates in Norway' and get a formatted time-series CSV in 10 seconds. That's the entire product. Statista charges €490/month for literally the same thing.

Still early and has rough edges: some queries fail, source citations need work, and the UI is... functional. But it works well enough that I've stopped paying for Statista. Which is wild because most of this data is already public anyway.

Free tier is live at qoery.com. What data would you search for first, and did it actually work?

Show HN: Query 50M statistics in plain English

https://qoery.com

Hey HN,We built qoery because we were tired of downloading CSVs from the World Bank, Eurostat, OECD, and a dozen other portals every time we needed a simple statistic.Now you can just ask "What's France's GDP growth rate?" and get structured data back instantly. We've indexed 50M observations from ~10K sources into a single queryable interface.The technical challenge was less about NLP and more...

( Read More... | no comments | 2 points | on HN )

Show HN: StrateQueue- Bridge backtest and live trading with microsecond latency

https://github.com/StrateQueue/StrateQueue

My co-founder and I applied to YC this summer with a full quant platform - backtest, optimize, and deploy strategies all in one place. Regulatory complexity killed us. We had to pivot.While my co-founder moved on to other things, I kept working on the core problem: why is it so hard to go from backtest to live trading? Our original platform only supported one backtesting framework, and we acted...

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