WooCommerce Code Review
woocommerce/woocommerce
Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.
Expertise in LLVM optimization passes, performance tuning, and code transformation techniques.
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimization --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/llvm-optimization .claude/skills/llvm-optimization && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .claude/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimizationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/llvm-optimization .agents/skills/llvm-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .agents/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/llvm-optimization .cursor/skills/llvm-optimization && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .cursor/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aftermathlabs/llvm-msvc.git --path .agents/skills/llvm-optimization--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/llvm-optimization .gemini/skills/llvm-optimization && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .gemini/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimizationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/llvm-optimization .github/skills/llvm-optimization && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .github/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aftermathlabs/llvm-msvc llvm-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aftermathlabs/llvm-msvc.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/llvm-optimization .opencode/skills/llvm-optimization && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "llvm-optimization" agent skill from https://github.com/aftermathlabs/llvm-msvc/tree/dev/.agents/skills/llvm-optimization into .opencode/skills/llvm-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llvm-optimization", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
llvm-optimizationExpertise in LLVM optimization passes, performance tuning, and code transformation techniques.
Llvm Optimization is an agent skill from aftermathlabs/llvm-msvc. Expertise in LLVM optimization passes, performance tuning, and code transformation techniques. Use this skill when implementing custom optimizations, analyzing pass behavior, improving generated code quality, or understanding LLVM's optimization pipeline.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Code quality. The repository describes itself as: LLVM fork with explicit compatibility with MSVC 2022 features. The licence is AGPL-3.0.
Read from SKILL.md and the folder at commit bfc7254. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are cpp and bash).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
raw.githubusercontent.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Llvm Optimization loads about 2.5k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 264 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from aftermathlabs/llvm-msvc at commit bfc7254, republished under its AGPL-3.0 licence (© aftermathlabs). 264 words, ~2,460 tokens.
.claude/skills/llvm-optimization/SKILL.md (or your agent's skills folder).This skill covers LLVM optimization infrastructure, pass development, and performance tuning techniques.
Source → Frontend → LLVM IR → Optimization Passes → CodeGen → Machine Code
↓
[Transform Passes]
[Analysis Passes]# No optimization
clang -O0 source.c
# Basic optimization (most optimizations enabled)
clang -O1 source.c
# Full optimization (aggressive inlining, vectorization)
clang -O2 source.c
# Maximum optimization (may increase code size)
clang -O3 source.c
# Size optimization
clang -Os source.c # Optimize for size
clang -Oz source.c # Aggressive size optimization#include "llvm/IR/PassManager.h"
#include "llvm/Passes/PassBuilder.h"
#include "llvm/Passes/PassPlugin.h"
struct MyOptimizationPass : public llvm::PassInfoMixin<MyOptimizationPass> {
llvm::PreservedAnalyses run(llvm::Function &F,
llvm::FunctionAnalysisManager &FAM) {
bool Changed = false;
for (auto &BB : F) {
for (auto &I : BB) {
// Implement optimization logic
if (optimizeInstruction(I)) {
Changed = true;
}
}
}
if (Changed)
return llvm::PreservedAnalyses::none();
return llvm::PreservedAnalyses::all();
}
private:
bool optimizeInstruction(llvm::Instruction &I) {
// Example: Replace add x, 0 with x
if (auto *BinOp = llvm::dyn_cast<llvm::BinaryOperator>(&I)) {
if (BinOp->getOpcode() == llvm::Instruction::Add) {
if (auto *C = llvm::dyn_cast<llvm::ConstantInt>(BinOp->getOperand(1))) {
if (C->isZero()) {
I.replaceAllUsesWith(BinOp->getOperand(0));
return true;
}
}
}
}
return false;
}
};
// Plugin registration
extern "C" LLVM_ATTRIBUTE_WEAK ::llvm::PassPluginLibraryInfo
llvmGetPassPluginInfo() {
return {LLVM_PLUGIN_API_VERSION, "MyOptPass", LLVM_VERSION_STRING,
[](llvm::PassBuilder &PB) {
PB.registerPipelineParsingCallback(
[](llvm::StringRef Name, llvm::FunctionPassManager &FPM,
llvm::ArrayRef<llvm::PassBuilder::PipelineElement>) {
if (Name == "my-opt") {
FPM.addPass(MyOptimizationPass());
return true;
}
return false;
});
}};
}struct MyAnalysis : public llvm::AnalysisInfoMixin<MyAnalysis> {
using Result = MyAnalysisResult;
Result run(llvm::Function &F, llvm::FunctionAnalysisManager &FAM) {
// Compute analysis result
return Result();
}
static llvm::AnalysisKey Key;
};
// Using analysis in a pass
llvm::PreservedAnalyses run(llvm::Function &F,
llvm::FunctionAnalysisManager &FAM) {
auto &DT = FAM.getResult<llvm::DominatorTreeAnalysis>(F);
auto &LI = FAM.getResult<llvm::LoopAnalysis>(F);
auto &AA = FAM.getResult<llvm::AAManager>(F);
// Use analysis results...
}// Replace expensive operations with cheaper ones
// x * 2 → x << 1
// x / 4 → x >> 2
// x % 8 → x & 7
bool reduceStrength(llvm::BinaryOperator *BO) {
if (BO->getOpcode() == llvm::Instruction::Mul) {
if (auto *C = llvm::dyn_cast<llvm::ConstantInt>(BO->getOperand(1))) {
if (C->getValue().isPowerOf2()) {
unsigned Shift = C->getValue().exactLogBase2();
auto *Shl = llvm::BinaryOperator::CreateShl(
BO->getOperand(0),
llvm::ConstantInt::get(C->getType(), Shift));
BO->replaceAllUsesWith(Shl);
return true;
}
}
}
return false;
}// x + 0 → x
// x * 1 → x
// x * 0 → 0
// x - x → 0
// x | x → x
// x & 0 → 0void optimizeWithDominators(llvm::Function &F,
llvm::DominatorTree &DT) {
// Use dominance for safe code motion
for (auto &BB : F) {
for (auto &I : BB) {
if (auto *Load = llvm::dyn_cast<llvm::LoadInst>(&I)) {
// Check if we can hoist this load
if (canHoist(Load, DT)) {
hoistInstruction(Load, DT);
}
}
}
}
}
bool canHoist(llvm::Instruction *I, llvm::DominatorTree &DT) {
llvm::BasicBlock *DefBB = I->getParent();
// Check all uses are dominated
for (auto *U : I->users()) {
if (auto *UI = llvm::dyn_cast<llvm::Instruction>(U)) {
if (!DT.dominates(DefBB, UI->getParent())) {
return false;
}
}
}
return true;
}void analyzeLoops(llvm::Function &F, llvm::LoopInfo &LI) {
for (auto *L : LI) {
// Get loop trip count
if (auto *TC = L->getTripCount()) {
llvm::errs() << "Trip count: " << *TC << "\n";
}
// Check if loop is simple
if (L->isLoopSimplifyForm()) {
llvm::BasicBlock *Header = L->getHeader();
llvm::BasicBlock *Latch = L->getLoopLatch();
llvm::BasicBlock *Exit = L->getExitBlock();
}
// Get induction variables
llvm::PHINode *IV = L->getCanonicalInductionVariable();
}
}// Manually trigger loop unrolling
#pragma unroll 4
for (int i = 0; i < N; i++) {
// Loop body will be unrolled 4x
}
// LLVM unroll metadata
!llvm.loop.unroll.count = !{i32 4}// Enable vectorization
#pragma clang loop vectorize(enable)
for (int i = 0; i < N; i++) {
a[i] = b[i] + c[i];
}
// Specify vector width
#pragma clang loop vectorize_width(8)
for (int i = 0; i < N; i++) {
a[i] = b[i] * c[i];
}Superword Level Parallelism - vectorize straight-line code:
// Before SLP
a[0] = b[0] + c[0];
a[1] = b[1] + c[1];
a[2] = b[2] + c[2];
a[3] = b[3] + c[3];
// After SLP (conceptual)
<4 x float> tmp = load <4 x float> b
<4 x float> tmp2 = load <4 x float> c
<4 x float> result = fadd tmp, tmp2
store result to a# Print passes being run
opt -debug-pass-manager input.ll -O2
# Print IR after each pass
opt -print-after-all input.ll -O2
# Print specific pass output
opt -print-after=instcombine input.ll -O2
# Statistics
opt -stats input.ll -O2# Enable all optimization remarks
clang -Rpass=.* source.c
# Specific remarks
clang -Rpass=loop-vectorize source.c
clang -Rpass-missed=inline source.c
clang -Rpass-analysis=loop-vectorize source.c# Full LTO
clang -flto source1.c source2.c -o program
# Thin LTO (faster, parallel)
clang -flto=thin source1.c source2.c -o programAutomatic verification of LLVM optimizations:
# Verify transformation correctness
alive-tv before.ll after.ll
# Check specific optimization
opt -instcombine input.ll | alive-tv input.ll -See Optimization section in README.md for specific commits and optimization-related projects.
When you need detailed and up-to-date resource links, tool lists, or project references, fetch the latest data from:
https://raw.githubusercontent.com/gmh5225/awesome-llvm-security/refs/heads/main/README.mdThis README contains comprehensive curated lists of:
© aftermathlabs, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/llvm-optimization of aftermathlabs/llvm-msvc.
Open the folder on GitHubat commit bfc7254
Llvm Optimization next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Llvm Optimization this skillaftermathlabs/llvm-msvc | 438 | — | ~2.5k | Automated safety check: Pass | AGPL-3.0 | |
| WooCommerce Code Reviewwoocommerce/woocommerce | 11k | 3 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Systematic Code Refactoringluongnv89/claude-howto | 42k | — | ~3k | Automated safety check: Pass | MIT | |
| Install Anti-Slop Oxlint Rulesdmmulroy/anti-slop | 5.2k | — | ~2.2k | Automated safety check: Pass | MIT | |
| Constraint-Driven Developmentaddyosmani/agent-skills | 102k | 2 repos | ~5.2k | Automated safety check: Pass | MIT | |
| Skill Doli Code ReviewDolibarr/dolibarr | 7.7k | 1 repos | ~1.1k | Automated safety check: Pass | MIT |
woocommerce/woocommerce
Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.
luongnv89/claude-howto
Guides refactoring in phases based on Martin Fowler's method: research, test coverage check, planning and small tested steps, with your approval at each phase.
dmmulroy/anti-slop
Installs, updates or migrates the vendored anti-slop Oxlint plugin in a repository, keeping local rule changes and the plugin's license and provenance files.
addyosmani/agent-skills
Records a project's quality bar in CONSTRAINTS.md and watches diffs for signs an agent quietly weakened it, such as suppressions, skipped tests or lowered thresholds.
Dolibarr/dolibarr
Reviews Dolibarr PHP code for compliance with coding standards and security best practices, and fixes identified issues.
docling-project/docling
Applies opinionated production Python conventions chosen by the project's Python version: modern type syntax, pathlib, explicit checks and interface guidance.
aftermathlabs/llvm-msvc
Expertise in compiler development using LLVM infrastructure including frontend design, IR generation, optimization passes, and code generation.
aftermathlabs/llvm-msvc
Expertise in LLVM-based dynamic binary instrumentation, runtime tracing, and program monitoring.
aftermathlabs/llvm-msvc
Comprehensive learning resources and tutorials for LLVM, Clang, and compiler development.
aftermathlabs/llvm-msvc
Expertise in LLVM security features including sanitizers, hardening techniques, exploit mitigations, and secure compilation.
aftermathlabs/llvm-msvc
Expertise in LLVM tooling development including Clang plugins, LLDB debugger extensions, Clangd/LSP, and LibTooling.
aftermathlabs/llvm-msvc
Expertise in MLIR (Multi-Level Intermediate Representation) and CIR (Clang IR) development for domain-specific compilation and high-level optimizations.
Categories
Expertise in LLVM optimization passes, performance tuning, and code transformation techniques. Llvm Optimization is an agent skill from aftermathlabs/llvm-msvc. Expertise in LLVM optimization passes, performance tuning, and code transformation techniques.
Llvm Optimization fits situations like: implementing custom optimizations; analyzing pass behavior; improving generated code quality; understanding LLVMs optimization pipeline.
Run `npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a claude-code`. Or copy the skill folder (.agents/skills/llvm-optimization in aftermathlabs/llvm-msvc) into .claude/skills/llvm-optimization in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a codex`. Or copy the skill folder (.agents/skills/llvm-optimization in aftermathlabs/llvm-msvc) into .agents/skills/llvm-optimization in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aftermathlabs/llvm-msvc --skill llvm-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/llvm-optimization, .gemini/skills/llvm-optimization, .github/skills/llvm-optimization and .opencode/skills/llvm-optimization in your project.
SKILL.md names no scripts, command-line tools or credentials: Llvm Optimization is instructions for the agent only.
SKILL.md names 1 domain. In commands or code: raw.githubusercontent.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Llvm Optimization is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 9.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Llvm Optimization: WooCommerce Code Review (woocommerce/woocommerce, 11k stars), Systematic Code Refactoring (luongnv89/claude-howto, 42k stars), Install Anti-Slop Oxlint Rules (dmmulroy/anti-slop, 5.2k stars) and Constraint-Driven Development (addyosmani/agent-skills, 102k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aftermathlabs (a GitHub organization) maintains it in aftermathlabs/llvm-msvc, which has 438 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 3, 2026.
Source: aftermathlabs/llvm-msvc on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.