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C Cpp To Lean4 Translator

Community
ArabelaTso
c-cpp-to-lean4-translator

Translate C or C++ programs into equivalent Lean4 code, preserving program semantics and ensuring the generated code is well-typed, executable, and can run successfully. Use when the user asks to convert C/C++ code to Lean4, port C/C++ programs to Lean4, translate imperative code to functional Lean4, or create Lean4 versions of C/C++ algorithms.

Overview

PublisherArabelaTso
RepositorySkills-4-SE
Skill namec-cpp-to-lean4-translator
Stars
258
Forks
25
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ArabelaTso on GitHub. Read the source before you install it.

Installation

Install the C Cpp To Lean4 Translator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/c-cpp-to-lean4-translator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ArabelaTso/Skills-4-SE.git /tmp/Skills-4-SE
mkdir -p .claude/skills
cp -r /tmp/Skills-4-SE/skills/c-cpp-to-lean4-translator .claude/skills/c-cpp-to-lean4-translator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable C Cpp To Lean4 Translator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads C Cpp To Lean4 Translator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so C Cpp To Lean4 Translator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

C/C++ to Lean4 Translator

Overview

Transform C or C++ programs into equivalent Lean4 code that preserves the original semantics while leveraging Lean4's functional programming paradigm, strong type system, and proof capabilities.

Translation Workflow

Step 1: Analyze Input Code

Understand the C/C++ program structure and semantics:

  1. Identify program components:

    • Functions and their signatures
    • Data structures (structs, classes, arrays)
    • Control flow patterns (loops, conditionals)
    • Memory management (allocation, pointers)
    • I/O operations
    • Dependencies and includes
  2. Understand semantics:

    • What does the program compute?
    • What are the inputs and outputs?
    • Are there side effects?
    • What are the invariants and preconditions?
  3. Note translation challenges:

    • Pointer arithmetic
    • Mutable state
    • Imperative loops
    • Manual memory management
    • Undefined behavior

Step 2: Design Lean4 Structure

Plan the Lean4 equivalent before writing code:

  1. Choose appropriate types:

    • Int for signed integers
    • Nat for unsigned integers and array indices
    • Float for floating-point numbers
    • Array for dynamic arrays
    • List for linked lists
    • Custom structure types for structs/classes
  2. Determine purity:

    • Pure functions: return values directly
    • Side effects: use IO monad
    • Mutable state: use IO.Ref or ST monad
  3. Plan control flow translation:

    • Loops → Recursive functions
    • Mutable variables → Function parameters
    • Early returns → Conditional expressions
  4. Handle memory:

    • Stack allocation → Direct values
    • Heap allocation → Automatic memory management
    • Pointers → Direct values or references

Step 3: Translate Code

Follow these translation principles:

Functions

Pattern: Pure function

c
// C/C++
int add(int a, int b) {
    return a + b;
}
lean
-- Lean4
def add (a b : Int) : Int :=
  a + b

Pattern: Function with side effects

c
// C/C++
void printSum(int a, int b) {
    printf("%d\n", a + b);
}
lean
-- Lean4
def printSum (a b : Int) : IO Unit :=
  IO.println (a + b)
Control Flow

Pattern: If-else

c
// C/C++
int max(int a, int b) {
    if (a > b) return a;
    else return b;
}
lean
-- Lean4
def max (a b : Int) : Int :=
  if a > b then a else b

Pattern: For loop → Tail recursion

c
// C/C++
int sum(int n) {
    int result = 0;
    for (int i = 0; i < n; i++) {
        result += i;
    }
    return result;
}
lean
-- Lean4
def sum (n : Nat) : Nat :=
  let rec loop (i acc : Nat) : Nat :=
    if i >= n then acc
    else loop (i + 1) (acc + i)
  loop 0 0

Pattern: While loop → Recursion

c
// C/C++
int factorial(int n) {
    int result = 1;
    while (n > 1) {
        result *= n;
        n--;
    }
    return result;
}
lean
-- Lean4
def factorial (n : Nat) : Nat :=
  let rec loop (n acc : Nat) : Nat :=
    if n <= 1 then acc
    else loop (n - 1) (acc * n)
  loop n 1
Data Structures

Pattern: Struct

c
// C/C++
struct Point {
    int x;
    int y;
};
lean
-- Lean4
structure Point where
  x : Int
  y : Int
  deriving Repr

Pattern: Array

c
// C/C++
int arr[5] = {1, 2, 3, 4, 5};
lean
-- Lean4
def arr : Array Int := #[1, 2, 3, 4, 5]
Pointers and References

Key principle: Lean4 doesn't have raw pointers. Translate based on usage:

  • Read-only pointers: Pass by value
  • Output parameters: Return values (use tuples for multiple returns)
  • Mutable references: Use IO.Ref or return new values
c
// C/C++ - Output parameter
void swap(int* a, int* b) {
    int temp = *a;
    *a = *b;
    *b = temp;
}
lean
-- Lean4 - Return tuple
def swap (a b : Int) : Int × Int :=
  (b, a)

Step 4: Ensure Type Correctness

Lean4's type system is strict. Address common type issues:

  1. Integer types:

    • Use Nat for non-negative values (array indices, counts)
    • Use Int for potentially negative values
    • Convert explicitly: n.toNat, n.toInt
  2. Array bounds:

    • Lean4 requires proof of valid indices
    • Use safe accessors: arr.get?, arr[i]?
    • Or use arr[i]! with runtime check
  3. Division:

    • Natural number division: n / m (rounds down)
    • Integer division: use Int.div
    • Handle division by zero explicitly
  4. Type annotations:

    • Add explicit types when inference fails
    • Use : Type for clarity

Step 5: Test and Verify

Ensure the translated code works correctly:

  1. Compile check:

    bash
    lake build
  2. Create test cases:

    lean
    #eval add 2 3        -- Should output 5
    #eval factorial 5    -- Should output 120
  3. Compare outputs:

    • Run original C/C++ program
    • Run translated Lean4 program
    • Verify outputs match for same inputs
  4. Handle edge cases:

    • Empty arrays
    • Zero values
    • Negative numbers
    • Boundary conditions

Step 6: Optimize and Refine

Improve the translated code:

  1. Use Lean4 idioms:

    • Replace manual recursion with List.foldl, Array.foldl
    • Use pattern matching instead of nested if-else
    • Leverage standard library functions
  2. Add documentation:

    lean
    /-- Calculate the sum of first n natural numbers -/
    def sum (n : Nat) : Nat :=
      n * (n + 1) / 2
  3. Consider performance:

    • Use tail recursion for loops
    • Prefer Array over List for random access
    • Use @[inline] for small functions

Common Translation Patterns

For detailed patterns, see translation_patterns.md.

Quick Reference

C/C++Lean4
int xdef x : Int
unsigned int xdef x : Nat
float xdef x : Float
bool xdef x : Bool
char* strdef str : String
int arr[]def arr : Array Int
struct Sstructure S where
for (...)let rec loop ...
while (...)let rec loop ...
if (...) {...}if ... then ... else ...
switch (...)match ... with
return xx (last expression)
void f()def f : IO Unit
printf(...)IO.println ...

Examples

Example 1: Simple Algorithm

C/C++ Input:

c
int gcd(int a, int b) {
    while (b != 0) {
        int temp = b;
        b = a % b;
        a = temp;
    }
    return a;
}

Lean4 Output:

lean
def gcd (a b : Nat) : Nat :=
  if b = 0 then a
  else gcd b (a % b)

Example 2: Array Processing

C/C++ Input:

c
int findMax(int arr[], int size) {
    int max = arr[0];
    for (int i = 1; i < size; i++) {
        if (arr[i] > max) {
            max = arr[i];
        }
    }
    return max;
}

Lean4 Output:

lean
def findMax (arr : Array Int) : Option Int :=
  if arr.isEmpty then
    none
  else
    some (arr.foldl max arr[0]!)

Example 3: Struct with Methods

C/C++ Input:

cpp
struct Rectangle {
    int width;
    int height;

    int area() {
        return width * height;
    }

    int perimeter() {
        return 2 * (width + height);
    }
};

Lean4 Output:

lean
structure Rectangle where
  width : Nat
  height : Nat
  deriving Repr

def Rectangle.area (r : Rectangle) : Nat :=
  r.width * r.height

def Rectangle.perimeter (r : Rectangle) : Nat :=
  2 * (r.width + r.height)

Example 4: I/O Program

C/C++ Input:

c
#include <stdio.h>

int main() {
    int n;
    printf("Enter a number: ");
    scanf("%d", &n);
    printf("Factorial: %d\n", factorial(n));
    return 0;
}

Lean4 Output:

lean
def factorial (n : Nat) : Nat :=
  if n <= 1 then 1
  else n * factorial (n - 1)

def main : IO Unit := do
  IO.print "Enter a number: "
  let input ← IO.getStdIn >>= (·.getLine)
  match input.trim.toNat? with
  | some n =>
    IO.println s!"Factorial: {factorial n}"
  | none =>
    IO.println "Invalid input"

Best Practices

  1. Start simple: Translate basic functions first, then build up complexity
  2. Preserve semantics: Ensure the Lean4 code computes the same results
  3. Use types wisely: Leverage Lean4's type system for correctness
  4. Embrace immutability: Prefer pure functions over mutable state
  5. Test thoroughly: Verify outputs match for various inputs
  6. Document assumptions: Note any semantic differences or limitations
  7. Leverage standard library: Use built-in functions when available
  8. Handle errors gracefully: Use Option or Except for error cases

Limitations and Considerations

  1. Undefined behavior: C/C++ undefined behavior must be handled explicitly in Lean4
  2. Performance: Functional code may have different performance characteristics
  3. Concurrency: C/C++ threading requires different approaches in Lean4
  4. Low-level operations: Bit manipulation and pointer arithmetic need careful translation
  5. External libraries: C/C++ library calls may not have direct Lean4 equivalents
  6. Macros: C preprocessor macros need manual translation
  7. Templates: C++ templates translate to Lean4 generics differently

Resources

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the C Cpp To Lean4 Translator AI skill do?

Translate C or C++ programs into equivalent Lean4 code, preserving program semantics and ensuring the generated code is well-typed, executable, and can run successfully. Use when the user asks to convert C/C++ code to Lean4, port C/C++ programs to Lean4, translate imperative code to functional Lean4, or create Lean4 versions of C/C++ algorithms.

Why use C Cpp To Lean4 Translator on TypingMind?

Because you install it once and use it with any model. C Cpp To Lean4 Translator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install C Cpp To Lean4 Translator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArabelaTso/Skills-4-SE/tree/main/skills/c-cpp-to-lean4-translator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use C Cpp To Lean4 Translator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with C Cpp To Lean4 Translator?

As many as you like. As long as a model supports skills, you can use C Cpp To Lean4 Translator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the C Cpp To Lean4 Translator AI skill free?

Yes. It is published on GitHub by ArabelaTso under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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