Perf Reviewer

Performance Reviewer

Review code for performance issues and run cross-language benchmarks.

Quick Start

Run benchmarks comparing AILANG vs Python vs compiled Go:

# Run all standard benchmarks
.claude/​skills/​perf-reviewer/​scripts/​benchmark.sh

# Run specific benchmark
.claude/​skills/​perf-reviewer/​scripts/​benchmark.sh fibonacci

# Review code for performance issues
# Just ask: "review this code for performance"

When to Use This Skill

Invoke this skill when:

• User asks to "benchmark" or "compare performance"
• User wants to compare AILANG vs Python vs Go
• User asks to "review for performance" or "optimize"
• User mentions "slow", "performance", "bottleneck"
• After implementing compute-intensive code
• Before releases to verify no performance regressions

Available Scripts

scripts/​benchmark.sh [benchmark_name]

Run cross-language benchmarks comparing AILANG interpreted, Python, and AILANG compiled to Go.

Available benchmarks: fibonacci, sort, transform, all

Output: Timing comparisons, speedup ratios, and recommendations.

scripts/​profile_ailang.sh <file.ail>

Profile an AILANG file with timing breakdown by compilation phase.

Workflow

1. Performance Review (Code Analysis)

When reviewing code, check against these principles (see resources/​principles.md):

Critical checks:

1. Algorithmic complexity - Is there an O(n log n) solution for O(n²) code?
2. Batch operations - Can multiple operations be combined?
3. Memory allocation - Are allocations inside hot loops?
4. Data layout - Are frequently-accessed fields colocated?

Quick checklist:

[ ] No O(n²) where O(n log n) exists
[ ] Batch APIs for repeated operations
[ ] Allocations hoisted outside loops
[ ] Hot paths optimized, edge cases separate
[ ] No unnecessary string formatting in loops

2. Benchmarking (Cross-Language Comparison)

Run benchmarks:

# Full benchmark suite
.claude/​skills/​perf-reviewer/​scripts/​benchmark.sh all

# Single benchmark
.claude/​skills/​perf-reviewer/​scripts/​benchmark.sh fibonacci

Interpret results:

3. Profiling (Phase Breakdown)

.claude/​skills/​perf-reviewer/​scripts/​profile_ailang.sh examples/​compute_heavy.ail

Phase timing helps identify:

• Slow parsing -> complex syntax
• Slow type checking -> deep type inference
• Slow evaluation -> algorithmic issues

Performance Principles Summary

From resources/​principles.md:

Resources

• resources/​principles.md - Full performance principles (Abseil-inspired)
• resources/​go_patterns.md - Go-specific optimization patterns

Notes

• Compiled AILANG (Go) should be 10-100x faster than interpreted
• Python comparison provides baseline for interpreted languages
• Always profile real workloads, not just microbenchmarks