setup

Topics in the source

• /autoresearch-agent:setup — Create New Experiment
• Usage
• What It Does
• If arguments provided
• If no arguments (interactive mode)
• Listing
• Built-in Evaluators
• After Setup

Set up a new autoresearch experiment with all required configuration. Pass them directly to the setup script: Collect each parameter one at a time: 1. Domain — Ask: "What domain? (engineering, marketing, content, prompts, custom)" 2. Name — Ask: "Experiment name? (e.g., api-speed, blog-titles)" 3. Target file — Ask: "Which file to optimize?" Verify it exists. 4. Eval command — Ask: "How to measure it? (e.g., pytest bench.py, python evaluate.py)" 5. Metric — Ask: "What metric does the eval output? (e.g., p50ms, ctrscore)" 6. Direction — Ask: "Is lower or higher better?" 7. Evaluator (optional) — Show built-in evaluators. Ask: "Use a built-in evaluator, or your own?" 8. Scope — Ask: "Store in project (.autoresearch/) or user (/.autoresearch/)?" Then run setupexperiment.py with the collected parameters. | Name | Metric | Use Case | |------|--------|----------| | benchmarkspeed | p50ms (lower) | Function/API execution time | | benchmarksize | sizebytes (lower) | File, bundle, Docker image size | | testpassrate | passrate (higher) | Test suite pass percentage | | buildspeed | buildseconds (lower) | Build/compile/Docker build time | | memoryusage | peakmb (lower) | Peak memory during exe

This is an excerpt. Refer to the complete source and its current requirements.