Jacquard
Jacquard is a small programming language designed for running, reviewing, and trusting programs written by machine-learning models and reviewed by people.
Jacquard
What is Jacquard?
Jacquard vs Similar AI Tools
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How to use Jacquard?
- 1Install the binary: curl -fsSL https://raw.githubusercontent.com/jbwinters/jacquard-lang/jacquard-core-0.1-rc3/scripts/install.sh | sh
- 2Run a program: jac run ~/.local/share/jacquard/demos/basics/m1-fact.jac
- 3Check effects: jac check FILE.jac --manifest
- 4Run tests: jac test TESTS.jac
Jacquard Key Features
- Algebraic effects with deep, multi-shot handlers
- Type-and-effect rows for capability enforcement
- Content-addressed definitions with structural hashing
- Discrete probabilistic programming as a library
- Native AOT compilation emitting C
Jacquard Use Cases
- Reviewing AI-generated code for side effects and uncertainty
- Simulating programs under multiple world models
- Exact probabilistic inference via enumeration
- Program repair as Bayesian inference
Jacquard Pricing & Free Credits
Jacquard currently operates on a Free model.
This tool is completely free to use
Jacquard Pros & Cons
Pros
- Language-level effect tracking and enforcement
- Multi-shot handlers enable exact Bayesian inference
- Canonical identity ignores formatting and renames
- Built for trust in AI-generated code
Cons
- Research prototype, not production-ready
- Limited ecosystem and documentation
- Only core 0.1 semantic boundary defined
- No concurrency or JIT support
What is Jacquard best for?
- AI safety and review workflows
- Probabilistic programming research
- Safe effect management in generated code
Jacquard FAQ
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