Alternatives
Products that do what Lean4 proof that SSOT requires definition-time hooks and introspection does
I formalized the Single Source of Truth (SSOT) principle in Lean 4 (~2.1k LOC, zero sorry) and proved two core results: Structural SSOT is achievable only when a language provides definition-time hooks and runtime introspection. Macros/codegen (before definition) and reflection (after definition) are insufficient. These requirements are derived, not chosen: because structural facts are fixed at definition, derivation must occur at definition time and be introspectable to verify DOF = 1. Would appreciate review, critique, or independent checking of the Lean scripts.
- 1
To my knowledge, this is the first formally verified implementation of a 3D constructive solid geometry (CSG) operation: mesh intersection, implemented in Lean 4 and verified against a concise specification that pins down the surface of the resulting mesh exactly and guarantees practical well-formedness conditions on the triangulation. This project is also an experiment in avoiding having to trust AI-generated code. A human reviewer only needs to read 93 lines of formal specification and run the Lean checker to certify the correctness of the kernel, skipping the intricate 1000+ lines of…
Jul 2026 · github.com
- 2FP
This project aims to formalize the first volume of Prof. Bertrand Russell’s Principia Mathematica using the Lean theorem prover. Throughout the formalization, I tried to rigorously follow Prof. Russell’s proof, with no or little added statements from my side, which were only necessary for the formalization but not the logical argument. Should you notice any inaccuracy (even if it does not necessarily falsify the proof), please let me know as I would like to proceed with the same spirit of rigour. Before starting this project, I had already found Prof. Elkind’s formalization of the Principia…
2025 · github.com
- 3FV
2025 · github.com
- 4
At Cajal (YC W26) we’re excited to share Talos (https://github.com/cajal-technologies/talos), an open source framework for formal verification of WebAssembly modules in Lean. AI is now writing tons of the code that gets pushed to production. As code generation gets cheaper, verification becomes the bottleneck. We believe in a future where every piece of software comes with a mathematical proof that it does what its author intended - in doing so, eliminating many classes of exploits. Talos is part of the foundation for that. Talos provides a Wasm interpreter optimized for…
Jun 2026 · github.com
- 5AH
Long-simmering side project that is finally ready to see the light. HAMTs are a cool persistent data structure and implementing one has been a lot of fun. Beyond the code, there is likely some value in the extensive and largely complete implementation docs; basic benchmarks are linked in the README, too. Kind of aiming to be "the libavl for HAMTs". That is obviously a high and aspirational bar but a distinct possibility if it stirs up a little interest and/or contribution. Anyways, it's time for this to go out, collect feedback and maybe even some use outside of toy projects. Let me…
2023 · github.com
- 6CA
We've been building Crust (https://crustjs.com/), a TypeScript-first, Bun-native CLI framework with zero dependencies. It's been powering our core product internally for a while, and we're now open-sourcing it. The problem we kept running into: existing CLI frameworks in the JS ecosystem are either minimal arg parsers where you wire everything yourself, or heavyweight frameworks with large dependency trees and Node-era assumptions. We wanted something in between. What Crust does differently: - Full type inference from definitions — args and flags are inferred automatically. No…
Mar 2026 · github.com
- 7UR
This project is inspired by some of the asserts in Unreal engine. Due to reliance on core_intrinsics it is necessary to develop using nightly Rust, but there are stubs in place so a production build will not require nightly. I recently released version 0.2 which includes no_std support and adds optional log message arguments to the ensure macro.
2024 · github.com
- 8PS
Hi HN, I turned the freshly published paper “The Constructor Theory of Time” by David Deutsch and Chiara Marletto (arXiv, 13 May 2025) into an executable Python library. What you’ll find • One-to-one translation of the paper’s formalism: Substrates, Attributes, Tasks, Constructors, and task-algebra operators • Possibility / impossibility predicates and counterfactuals encoded exactly as defined • Test suite that mirrors every lemma and example (>95 % coverage, mypy-typed) • Reproductions of key results: time-keeping substrates, irreversibility proofs, quantum branching tasks, and a…
2025 · github.com
- 9ZK
2019 · zkwasm.kobi.one
- 10AA
I started writing this book 10 years ago in JavaScript, got through a few chapters (asymptotic notation, basic techniques, start of sorting), and then abandoned it. Recently I picked it back up, converted everything to TypeScript, and used AI (Zenflow [1] + Claude Opus 4.6) to complete the remaining chapters. I provided the structure, direction, and initial chapters; the AI generated the bulk of the remaining content under a spec-driven workflow. The book covers roughly a first 1-2 year CS curriculum: sorting, dynamic programming, graph algorithms, trees, heaps, hash tables, and more. All…
Mar 2026 · amoilanen.github.io
- 11KO
We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…
2025 · github.com
- 12AN
When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai
- 13
Salt is a systems language with an embedded Z3 theorem prover that checks preconditions and postconditions at compile time. Arena memory, MLIR codegen, and C-level performance without the usual tradeoffs.
Jul 2026 · salt-lang.dev
- 14AW
I've been presenting at local meetups about Context Engineering, RAG, Skills, etc.. I even have a vbrownbag coming up on LinkedIn about this topic so I figured I would make a basic example that uses bedrock so I can use it in my talks or vbrownbags. Hopefully it's useful.
Apr 2026 · github.com
- 15CG
2019 · github.com
- 16SP
Current support for nonlinear inequalities in Lean is quite limited. This package attempts to solve this. It contains a collection of Lean4 tactics for proving polynomial inequalities via sum-of-squares (SOS) decompositions, powered by a Python backend. You can use it via Python or Lean. These tactics are significantly more powerful than `nlinarith` and `positivity` -- i.e., they can prove inequalities they cannot. In theory, they can be used to prove any of the following types of statements - prove that a polynomial is nonnegative globally - prove that a polynomial is nonnegative over a…
Apr 2026 · github.com
- 17EG
TLDR: A small, vendor-agnostic inference loop that turns token logprobs/perplexity/entropy into an extra pass and reasoning for LLMs. - Captures logprobs/top-k during generation, computes perplexity and token-level entropy. - Triggers at most one refine when simple thresholds fire; passes a compact “uncertainty report” (uncertain tokens + top-k alts + local context) back to the model. - In our tests on technical Q&A / math / code, a small model recovered much of “reasoning” quality at ~⅓ the cost while refining ~⅓ of outputs. I kept seeing “reasoning” models behave…
2025 · github.com
- 18TA
Hi community, we just released https://github.com/tonbo-io/typed-arrow. When working with arrow-rs, we noticed that schemas are declared at runtime. This often leads to runtime errors and makes development less safe. typed-arrow takes a different approach: - Schemas are declared at compile time with Rust’s type system. - This eliminates runtime schema errors. - And introduces no runtime overhead — everything is checked and generated by the compiler. If you’ve run into Arrow runtime schema issues, and your schema is stable (not defined or switched at runtime), this project…
2025 · github.com
- 19AR
I've come to prefer modeling state machines with nested states, but implementing them by hand requires a large amount of error-prone boilerplate that obscures the important logic of the state machine. I found that the existing offerings in the Rust ecosystem - while inspiring - lacked a number of features that I was looking for, so I spent the last few months building moku. Feedback is welcome!
2025 · docs.rs
- 20GO
LLMs are better at being the "mouth" than the "brain" and I can prove it mathematically. I built a deterministic graph engine that offloads reasoning from the LLM. It reduces token usage by 89% and makes a tiny 0.8B model trace enterprise execution paths flawlessly. Here is the white paper and the reproducible benchmark.
Mar 2026 · github.com
- 21GA
It all started with a conversation among friends about limitations in current multi-agent orchestration frameworks. We faced issues like limited control over agent memory and state, complicated persistence, scaling problems, and lack of type safety in Python-based tools. These challenges inspired us to try something different. The result was GraphFlow, a Rust-based lean framework for orchestrating multi-agent workflows that's simple, scalable, and robust. Its key features include: Graph-based orchestration: Easily define workflows using nodes and edges. Lean Execution Engine: A minimal and…
2025 · github.com
- 22
Google Zanzibar datalog lang lets you describe concepts and express how they are related. I generalize it to DSL you can use on Lean4 (and other languages) this lets you represent a knowledge base you can construct, store and evaluate, have it under git and improve without big engines or relaying on external infrastructure. Google's Zanzibar paper: https://storage.googleapis.com/gweb-research2023-media/pubto...
Jul 2026 · github.com
- 23WL
Hey y’all, we’re really excited to share that we’re launching a new free, open source tool called Scale. It’s a highly-performant WebAssembly function runtime that enables composable, language-agnostic software development. TL;DR - Scale allows you to write functions in any language, then use them in any other language. It’s pretty exciting. We currently support Go and Rust, but TypeScript is coming soon and support for a handful of other languages is already in the works. We’d love to hear any feedback you have, so let us know what you think!
2023 · scale.sh
- 24IA
Hi HN, I thought this would be a good place to share a little puzzle I've been working on. Inception is a Rust library that helps you share behaviors in Rust using structural induction. Practically, this means that instead of having a derive macro for each behavior, a single derive can be used to enable any number of behaviors. It doesn't do this using runtime reflection, but rather type-level programming - so there is monomorphization across the substructures, and (at least in theory) no greater overhead than with macro expansion. While there are a lot of things missing still and the…
2025 · github.com
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