type-inference-engine

Implement and test type inference algorithms including Algorithm W and constraint-based inference

509 stars

Best use case

type-inference-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Implement and test type inference algorithms including Algorithm W and constraint-based inference

Teams using type-inference-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/type-inference-engine/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/computer-science/skills/type-inference-engine/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/type-inference-engine/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How type-inference-engine Compares

Feature / Agenttype-inference-engineStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Implement and test type inference algorithms including Algorithm W and constraint-based inference

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Type Inference Engine

## Purpose

Provides expert guidance on implementing type inference algorithms for programming language implementations.

## Capabilities

- Algorithm W implementation
- Constraint generation and solving
- Unification with occurs check
- Let-polymorphism (Hindley-Milner)
- Principal type computation
- Type error diagnosis

## Usage Guidelines

1. **Constraint Generation**: Generate type constraints from expressions
2. **Unification**: Implement unification algorithm
3. **Generalization**: Handle let-polymorphism
4. **Error Messages**: Generate informative type errors
5. **Testing**: Validate inference on test cases

## Tools/Libraries

- Language workbenches
- Constraint solvers
- Type inference libraries

Related Skills

typescript

509
from a5c-ai/babysitter

TypeScript configuration, strict mode, generics, and type utilities.

prototype-interaction

509
from a5c-ai/babysitter

Define and document prototype interactions, transitions, and hotspots

Ghidra/IDA Reverse Engineering Skill

509
from a5c-ai/babysitter

Deep integration with Ghidra and IDA Pro for binary analysis and reverse engineering

typespec-sdk-generator

509
from a5c-ai/babysitter

Microsoft TypeSpec-based API and SDK generation

typescript-sdk-specialist

509
from a5c-ai/babysitter

TypeScript SDK development with Node.js and browser support. Design SDK architecture, implement type-safe API clients, support ESM and CommonJS modules, and configure bundling for browsers.

Type Theory

509
from a5c-ai/babysitter

Expert skill in type theory foundations for implementing type systems including inference, checking, and subtyping

physics-engine

509
from a5c-ai/babysitter

Physics engine integration skill for rigid body dynamics and collision detection.

causal-inference-methods

509
from a5c-ai/babysitter

Apply propensity score methods, instrumental variables, difference-in-differences, and regression discontinuity designs for causal identification

music-prompt-engineering

509
from a5c-ai/babysitter

Optimize and format prompts specifically for AI music generation platforms like Suno and Udio, including platform-specific syntax and tag optimization

video-prompt-engineering

509
from a5c-ai/babysitter

Optimize prompts for AI video generation platforms including Sora, Runway, Pika, and Kling

meta-analysis-engine

509
from a5c-ai/babysitter

Skill for conducting meta-analyses of research findings

bayesian-inference-engine

509
from a5c-ai/babysitter

Bayesian probabilistic reasoning for prior specification, posterior computation, and belief updating