refactor: autoresearch-agent v2.0 — multi-experiment, multi-domain, real-world evaluators

Major rewrite based on deep study of Karpathy's autoresearch repo.

Architecture changes:
- Multi-experiment support: .autoresearch/{domain}/{name}/ structure
- Domain categories: engineering, marketing, content, prompts, custom
- Project-level (git-tracked, shareable) or user-level (~/.autoresearch/) scope
- User chooses scope during setup, not installation

New evaluators (8 ready-to-use):
- Free: benchmark_speed, benchmark_size, test_pass_rate, build_speed, memory_usage
- LLM judge (uses existing subscription): llm_judge_content, llm_judge_prompt, llm_judge_copy
- LLM judges call user's CLI tool (claude/codex/gemini) — no extra API keys needed

Script improvements:
- setup_experiment.py: --domain, --scope, --evaluator, --list, --list-evaluators
- run_experiment.py: --experiment domain/name, --resume, --loop, --single
- log_results.py: --dashboard, --domain, --format csv|markdown|terminal, --output

Results export:
- Terminal (default), CSV, and Markdown formats
- Per-experiment, per-domain, or cross-experiment dashboard view

SKILL.md rewritten:
- Clear activation triggers (when the skill should activate)
- Practical examples for each domain
- Evaluator documentation with cost transparency
- Simplified loop protocol matching Karpathy's original philosophy

engineering/autoresearch-agent/evaluators/build_speed.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+"""Measure build/compile time.
+DO NOT MODIFY after experiment starts — this is the fixed evaluator."""
+
+import subprocess
+import sys
+import time
+
+# --- CONFIGURE THESE ---
+BUILD_CMD = "npm run build"    # or: docker build -t test .
+CLEAN_CMD = ""                 # optional: npm run clean (run before each build)
+RUNS = 3                       # Number of builds to average
+# --- END CONFIG ---
+
+times = []
+
+for i in range(RUNS):
+    # Clean if configured
+    if CLEAN_CMD:
+        subprocess.run(CLEAN_CMD, shell=True, capture_output=True, timeout=60)
+
+    t0 = time.perf_counter()
+    result = subprocess.run(BUILD_CMD, shell=True, capture_output=True, timeout=600)
+    elapsed = time.perf_counter() - t0
+
+    if result.returncode != 0:
+        print(f"Build {i+1} failed (exit {result.returncode})", file=sys.stderr)
+        print(f"stderr: {result.stderr.decode()[:200]}", file=sys.stderr)
+        sys.exit(1)
+
+    times.append(elapsed)
+
+import statistics
+avg = statistics.mean(times)
+median = statistics.median(times)
+
+print(f"build_seconds: {median:.2f}")
+print(f"build_avg: {avg:.2f}")
+print(f"runs: {RUNS}")