git:20261023.d0d0254 to git:20261027.bf61c98

# Working on ADA

ADA is a Python package (`ada/`) with a command line (`ada`), a research

workflow (`ada/research/`: `ada init`, `ada build`, `ada verify`) and a

Streamlit app (`app.py`, `ada/ui.py`, `ada/home.py`).

[docs/architecture.md](docs/architecture.md) says which module does what.

## Setup and checks

```bash

ruff check .

python -m unittest discover -s tests

```

One test file: `python -m unittest discover -s tests -p "test_research_build.py"`.

CI runs the same checks on Python 3.11, 3.12 and 3.13, plus a job that builds

the wheel and runs `ada init`, `ada build` and `ada verify` from it.

## Conventions

- Calculations live in the engine modules and `ada/research/`, never in the

app; the app only draws results.

- Every number comes from pandas, SciPy or statsmodels and is shown with its

calculation. When something can't be computed honestly, refuse with a

reason instead of guessing.

- Builds are byte-stable: the same study.yml and data give the same files.

Don't put dates, temporary paths or random state in outputs.

- Code is formatted by hand: ruff check only, line length 110. Don't run

`ruff format`.

- Tests use `unittest`. A new rule needs a test, including how it behaves on

thin data.

- Docs, captions and messages are plain English in the present tense, with

no marketing words.

- Commit messages are one sentence that says what changed, such as "Skip

empty numeric columns in the value checks instead of failing on them".