feat(categorize): provider-agnostic account selector (auto-booking cascade, Tier 2) (#1779)

The core of the "optimal" RIP-4 categorizer, built to the researched 2026
architecture (retrieve → SELECT → escalate). Given a transaction, its underlag,
and the deterministic candidate accounts the engine already retrieved, the
model reasons and then CHOOSES from a closed set:

  - a retrieved candidate account (the known path), or
  - a standard business category → deterministic BAS account (the novel path,
    a first-time vendor with no candidate), or
  - needs_review (routed to a human, never auto-applied).

Because it picks from a closed enum, the model can't invent an account; the
account + VAT resolution stays deterministic and validated (the model chooses,
code resolves the numbers). It runs on any backend via getAiService()
.generateStructured — Bedrock or a local model.

Founder chose the optimal path (the model selects on every transaction, LLM
calls are fine), so confidence uses self-consistency: N samples (default 3),
majority vote, agreement fraction, combined with the model's stated confidence
and floored by the winning candidate's deterministic confidence — never the
model's verbalized confidence alone (systematically overconfident). reasoning
precedes choice in the schema (reason-before-choice); an unknown/hallucinated
choice degrades to needs_review.

13 unit tests (candidate/category/needs_review resolution, reverse-charge gating,
self-consistency majority + agreement + candidate floor, prompt/schema shape).
Not yet wired: Tier 1 candidate gathering + a route + the ApprovalCard UI.

Co-authored-by: Jakob Wennberg <311770904+jakobwennberg-oss@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>

DECISIONS.md

@@ -1142,3 +1142,4 @@ One line per decision: `[YYYY-MM-DD] <decision>: <why>`. Appended by agents and
 [2026-08-21] Korjournal distance suggestions via OSM (Nominatim+OSRM public endpoints) instead of Google Maps API: no key, no cost, AGPL-friendly, works self-hosted; addresses proxied server-side without identifiers and OSMF disclosed on the privacy page.
 [2026-08-21] Skeptic pass on #1778: routing endpoint switched from router.project-osrm.org (demo server, non-commercial only) to FOSSGIS routing.openstreetmap.de (fair use, attribution shown in UI); lookup click-gated instead of as-you-type per Nominatim's no-autocomplete policy; OSMF/FOSSGIS disclosed as independent recipients, not underbiträden.
 [2026-08-21] SCHABLONINTAKT_RATE_BY_CLOSING_YEAR backfilled 2020-2024 (SLR 30 Nov per Riksgalden: -0.09/-0.10/0.23 floored to 0.5 %, 1.94 %, 2.62 %) and the rate now resolves lazily (resolveSchablonintaktRate: 0 when no 212X account carried an opening balance): the table only covered 2025/2026 and the builder consulted it unconditionally, so every AB closing a pre-2025 year got a generic 500 at bokslut step 3 (126 open FY2024 periods on prod, incl. a byra trial). 2019 and earlier stay unmapped on purpose: the 100 %-of-SLR rule keys on beskattningsar STARTING 2019-01-01+ (prop. 2017/18:245), so a 2019 closing can be a brutet ar under the old 72 % factor. Unmapped-year-with-fonder now raises SCHABLONINTAKT_RATE_NOT_CONFIGURED (typed, 500 so runtime-error clustering still flags the missed December update) instead of INTERNAL_ERROR.
+[2026-08-21] RIP-4 "optimal" auto-booking cascade, Tier 2 = the provider-agnostic account SELECTOR (lib/agent/categorize/select-account.ts), built per the 2026 research (artifact dc0c2760): the model does NOT free-form a categorizer; it CHOOSES from a closed set — the deterministic candidate accounts (Tier 1) + the 19 standard business categories (each maps deterministically to a BAS account via getDefaultAccountForCategory) + "needs_review". So the model can't invent an account, account/VAT stays deterministic and validated, and it runs on any provider (Bedrock or a local model) via getAiService().generateStructured. Founder chose the optimal path (model selects on EVERY transaction, LLM calls are fine), so confidence uses SELF-CONSISTENCY (default 3 samples, majority vote, agreement fraction) combined with the model's stated confidence and floored by the winning candidate's deterministic confidence — never the model's verbalized confidence alone (research: systematically overconfident). reasoning field precedes choice in the schema (reason-before-choice). needs_review is never auto-applied. Calibration of the combined score → the auto-book/suggest/review gate is a later tier. Not yet wired: Tier 1 candidate gathering (counterparty templates + getSuggestedCategories) + a route + the ApprovalCard UI (next PRs).