Multi-Language Code Converter and Language Architect
Convert mixed, pseudo, or multi-language input into idiomatic production code, and select the right language(s) when none is dictated by the project.
When to Use This Skill
- Input mixes syntax from multiple languages (e.g.,
def and function in the same block, this. next to self., semicolons mixed with indentation-based blocks) - Input is pseudocode or natural language describing behavior plus code fragments
- User asks to "convert", "port", "translate", or "rewrite" code into another language
- A new project is starting with no language chosen and the user wants a recommendation
- A specification mixes config (YAML/TOML), SQL, and procedural logic that must be split into the right files
Operating Phases
Work through these phases in order. Skip a phase only when its premise does not apply (e.g., skip Phase 2 if a target language is already obvious from the project or user).
Phase 1 — Detect Existing Context
Before choosing a language, scan for signals in this priority order:
- Explicit user instruction — Always wins. If the user says "in Rust", produce Rust.
- Project manifests —
package.json, pyproject.toml / requirements.txt, Cargo.toml, go.mod, *.csproj, pom.xml / build.gradle, Gemfile, composer.json, tsconfig.json. The first one found generally dictates the target. - Source file extensions — Dominant extension in the workspace (
.ts, .py, .rs, .go, .java, .cs, .rb, .cpp, .kt, .swift). - Open editor / active file — Match the language of the file the user is editing.
- Nothing found — Proceed to Phase 2.
Phase 2 — Select Language (New Projects Only)
Run this only when Phase 1 yields no target. Map the goal to a domain, then pick the best fit:
| Domain | Strong default | Alternatives |
|---|
| -------- | ---------------- | -------------- |
| Systems / performance-critical | Rust | C++, Go, Zig |
| Web backend / API | TypeScript (Node) | Go, Python, Java, C#, Ruby |
| Web frontend / UI | TypeScript | JavaScript |
| Data / ML / AI | Python | R, Julia |
| Mobile (native) | Swift (iOS) / Kotlin (Android) | Dart/Flutter, React Native |
| Scripting / automation | Python | Bash (Unix), PowerShell (Windows) |
| Embedded / IoT | C / Rust | C++, MicroPython |
| Enterprise / type-heavy | Java / C# | TypeScript, Kotlin |
Decide single vs. polyglot:
- Frontend + backend → always two languages (TS frontend + backend of choice).
- Data pipeline + API → Python for data, Go/Node for API is a reasonable split.
- Otherwise prefer a single language — every additional language costs maintenance.
State the choice briefly (2–3 sentences per language) before writing code. Include one tradeoff the user should know.
Phase 3 — Parse the Mixed Input
For each fragment in the input:
- Classify — Which language(s) does the syntax most resemble? Tag fragments (Python-like, JS-like, SQL, shell, config, prose intent).
- Extract intent — What is this fragment trying to do? What flows in/out? What are the side effects?
- Flag ambiguities — If intent is genuinely unclear, list assumptions explicitly. If an assumption materially changes the output, ask before generating.
- Map — For each fragment, identify the idiomatic equivalent in the target language.
Phase 4 — Generate Code
- Use idiomatic syntax, formatting, and conventions for the target (PEP 8 for Python, rustfmt for Rust, gofmt for Go, Airbnb/standard for JS/TS, etc.).
- Apply the language's native error-handling pattern (exceptions,
Result, error returns, promises). Do not port one language's pattern into another. - Add types/type hints where the language supports or requires them.
- Produce runnable units (correct imports, package declarations, module headers) unless the input is clearly a snippet.
- If the input implies multiple files/modules, emit each as a separate labeled block.
- List required dependencies with install commands (
pip install …, npm install …, cargo add …).
Phase 5 — Respond in This Format
- Language decision (only if Phase 2 ran) — one short paragraph.
- Conversion notes — bullets covering: ambiguities, assumptions made, fragments that were restructured and why.
- Generated code — one labeled code block per file/module.
- Dependencies — install commands.
- Next steps (optional) — only if the input was a partial spec.
Gotchas
- Never silently drop input logic. If a fragment cannot be cleanly converted (e.g., Python's GIL-dependent threading patterns into JS), call it out in conversion notes and propose an equivalent — do not omit it.
- Never leave mixed syntax in output. If the output still contains
def and function together, this and self together, or print and console.log together, the conversion has failed. Re-check before responding. - Do not auto-convert config/data files (JSON, YAML, TOML, XML). Treat them as context unless the user explicitly asks for conversion.
- Error-handling idioms are not portable. Rewriting Python
try/except as Go try/catch produces non-compiling code. Translate to the target's native pattern (if err != nil, Result, etc.). - Indentation vs. braces. When converting from Python to a brace language (or vice versa), re-derive block structure from intent, not from the original whitespace — Python whitespace inside JS will silently change semantics.
- Don't invent dependencies. If the input uses
requests, the TS equivalent is fetch/axios — pick one and justify it; do not fabricate package names. - Honor explicit user language choice above all heuristics. Even if the project is Python, if the user says "give me this in Rust", produce Rust and note the mismatch.
- Prefer one language over polyglot unless justified. Splitting a small script into "Python for data + Node for API" is overkill — state the tradeoff and recommend the simpler path.
- Already-valid code in the right language ≠ conversion task. If the input is already clean code in the project's language, say so and offer style/quality improvements instead of rewriting it.
Mini Examples of Mixed Input This Skill Handles
- Python
import and if response.status_code == 200: inside a JS function () { … } wrapper with console.log — convert wholesale to one language. - Shell script containing free-form
SELECT * FROM users and loop through rows prose — split into a real shell driver plus a real SQL file, or fold into one language with a DB client. - Class definition mixing
def __init__(self), this.users, new ArrayList(), throw new Exception — pick one OO language and produce idiomatic class. - Pure natural-language spec ("POST /users, validate email regex, bcrypt cost=12, INSERT …, return 201") — treat as feature spec, generate full handler in target language.
- YAML config with embedded
if ENV == "production" and Math.max(5, cpu_count * 2) — split static config from runtime logic; emit a clean config file plus loader code.
References
- Tree-sitter (multi-language parsing reference):
- GitHub Linguist (language detection heuristics):
- Benchmarks Game (cross-language performance reference):
- TIOBE Index (language popularity):