Installs: 0
Used in: 1 repos
Updated: 1w ago
$
npx ai-builder add skill rand/benchInstalls to .claude/skills/bench/
Run performance benchmarks for RLM-Claude-Code. ## Commands ```bash # All benchmarks uv run pytest tests/benchmarks/ --benchmark-only # With comparison to baseline uv run pytest tests/benchmarks/ --benchmark-only --benchmark-compare # Save results uv run pytest tests/benchmarks/ --benchmark-only --benchmark-json=results.json # Specific benchmark uv run pytest tests/benchmarks/test_performance.py::test_complexity_classifier_latency --benchmark-only ``` ## Performance Targets | Component | Target | Measurement | |-----------|--------|-------------| | Complexity classifier | <50ms | `test_complexity_classifier_latency` | | REPL execution | <100ms | `test_repl_execution_latency` | | Trajectory render | <10ms/event | `test_trajectory_render_latency` | | Context externalization | <500ms | `test_context_externalization` | ## Profiling ```bash # CPU profiling python -m cProfile -s cumulative -m src.orchestrator --query "test" 2>&1 | head -50 # Memory profiling python -m memory_profiler src/orchestrator.py # Line profiling kernprof -l -v src/complexity_classifier.py ``` ## Cost Tracking Track token usage: ```bash uv run python -m src.tools.cost_tracker --trajectory /path/to/trajectory.json ``` Expected costs: - Simple query through RLM: ~$0.10-0.20 - Complex multi-file task: ~$0.30-0.50 - Deep verification (depth=2): ~$0.50-1.00
Quick Install
$
npx ai-builder add skill rand/benchDetails
- Type
- skill
- Author
- rand
- Slug
- rand/bench
- Created
- 1w ago