Detection reasoned on the shape of the data alone, so it could not tell a debit
column from a credit one: a file laid out `Date;Description;Credit;Debit` was
mapped by position and every sign of the import came out inverted — silently,
since the total is merely negated and no aggregate check notices.
A new `headerDictionary.ts` carries the FR/EN transaction dictionary (date,
description, amount, debit, credit, balance) plus the two matching helpers,
moved out of `csvAutoDetect.ts` whose holdings tables stay untouched: `montant`
is an exclusion token there and the primary amount keyword here, so the two
tables cannot be merged. Moving the generic helpers rather than exporting them
keeps the dependency one-way.
`csvAutoDetect` puts that layer in front of the shape heuristics. Labels resolve
the debit/credit order, the date, description and single-amount columns, and
give `detectHeader` a second signal for a header row carrying a bare number.
Every hint is a preference the data can veto — a labelled date column must still
parse, a labelled balance column is never excluded if it would leave nothing to
map — and a mute file (no header row, unknown labels) falls back to the shape
heuristics unchanged.
Files pairing unsigned amounts with an adjacent D/C indicator column are now
detected and REFUSED with a dedicated message, instead of being configured as
`positive_expense` and importing every deposit as an expense. Detection reports
that reason through `detectImportFormat`; `autoDetectConfig` keeps its previous
shape for the callers that only need the configuration.
Resolves#327
