feat: add autoresearch-agent — autonomous experiment loop for ML, prompt, code & skill optimization
Inspired by Karpathy's autoresearch. The agent modifies a target file, runs a
fixed evaluation, keeps improvements (git commit), discards failures (git reset),
and loops indefinitely — no human in the loop.
Includes:
- SKILL.md with setup wizard, 4 domain configs, experiment loop protocol
- 3 stdlib-only Python scripts (setup, run, log — 687 lines)
- Reference docs: experiment domains guide, program.md templates
Domains: ML training (val_bpb), prompt engineering (eval_score),
code performance (p50_ms), agent skill optimization (pass_rate).
Cherry-picked from feat/autoresearch-agent and rebased onto dev.
Fixes: timeout inconsistency (2x→2.5x), results.tsv tracking clarity,
zero-metric edge case, installation section aligned with multi-tool support.
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