experiment-suite

# Experiment Suite ## Overview End-to-end experiment package builder. **Single stage, full quality from the start.** The agent (Claude Code / Cursor / Aider / Codex / …) writes everything directly using its own tools (Write, Bash, WebFetch, …). This skill contains procedure + reference playbooks + figure-example scripts — no Python runtime, no LLM SDK. The substantive work is decomposed into reference playbooks under `references/`: | Reference | Topic | |---|---| | `references/00-incremental-execution.md` | how to do this without losing work: batches, persistence, resume — **read first** | | `references/01-design-depth.md` | what a real experiment design contains (motivation → hypothesis → datasets → baselines → metrics → ablations → budget) | | `references/01a-data-contract.md` | runtime dataset binding: source, access route, version, split, and reuse boundary | | `references/02-code-quality.md` | code-skeleton standards — runnable `model.py`, `data.py`, `train.py`, `evaluate.py` | | `references/03-results-protocol.md` | `results.json` schema; `measured` / `simulated` / `illustrative` provenance | | `references/04-publication-figures.md` | publication-grade charts, multi-panel layouts, taste rules | | `references/04a-figure-contract.md` | figure logic before plotting: conclusion, panel map, reviewer risk | | `references/04b-figure-qa.md` | export bundle, editable text, statistics and image-integrity QA | | `references/05-report-structure.md` | structured `experiment_repo...