LLVM Backend
Expert skill for LLVM integration including IR generation, optimization passes, and native code emission
npx skills add a5c-ai/babysitter --skill llvm-backend --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLVM Backend Skill ## Overview Expert skill for LLVM integration including IR generation, optimization passes, and native code emission. ## Capabilities - Generate LLVM IR from high-level AST/IR - Configure and run LLVM optimization passes - Implement custom LLVM passes - Handle LLVM type system mapping - Generate debug information (DWARF) - Configure target machine and code generation options - Implement LLVM JIT (ORC, MCJIT) integration - Handle cross-compilation target triples ## Target Processes - code-generation-llvm.js - jit-compiler-development.js - debugger-adapter-development.js - ir-design.js ## Dependencies - LLVM C++ API - llvm-sys bindings - Inkwell (Rust LLVM bindings) ## Usage Guidelines 1. **Type Mapping**: Establish clear mapping between source types and LLVM types 2. **SSA Form**: Leverage LLVM's SSA form; generate clean IR and let LLVM optimize 3. **Debug Info**: Generate debug info from the start using DIBuilder 4. **Optimization Levels**: Test with -O0 first, then enable optimizations incrementally 5. **Target Configuration**: Abstract target-specific code behind target triple configuration ## Output Schema ```json { "type": "object", "properties": { "llvmVer
- Overview
- Capabilities
- Target Processes
- Dependencies
- Usage Guidelines
- Output Schema
What does the LLVM Backend skill do?
Expert skill for LLVM integration including IR generation, optimization passes, and native code emission
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill llvm-backend --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.