feat: initial F∆I Law-Heatmap Phase 0 scaffold

First end-to-end-buildable cut of the pflicht-/graph-basierte
Wirkungsanalyse von Rechtsnormen, running on Ch∆In. Demo runs
without external dependencies and without a hub connection so
the methodology + UI stack can be reviewed before any Verbands-
Kooperation or Beirats-Validierung kicks in.

Tree layout

  MACHBARKEITSSTUDIE.md       v0.3 — pflicht-basierte Methodik,
                              4-Tier-Evidenz, 8 law*-Module
                              auf Ch∆In statt der alten F∆I-
                              Plattform.
  RUN.md                      one-page how-to-run.
  flows/durchstich-gewo-14.yaml
                              vertical Phase-0 flow: pull →
                              normalize → duties → citations →
                              cohort → skm → frust → benefit →
                              attribution → system.approval.
  app/                        Flutter macOS client, design
                              language pulled from fai_web
                              (ink #08090A, paper #F4F3EF,
                              petrol signal #2E8F9E). Mock
                              repository ships five fixture
                              norms with real source URLs and a
                              permanent T4 demo-banner so no
                              figure can be mistaken for a
                              validated one.

Module repos (separate, see chain-modules*/):

  text-akoma-normalize, text-deontic-extract, graph-citation-
  extract, text-readability-score, stats-cohort-size, graph-
  shapley-attribution, econ-skm-score, law-benefit-score.

What runs today

  - flutter analyze: 0 issues
  - flutter test: 2/2 (landing + nav-to-shell smoke)
  - flutter build macos (via app/build-macos.sh) and ad-hoc
    codesign, app launches and the Dart VM service comes up
  - native cargo test green on every module
  - cargo build --release --target wasm32-wasip2 produces a
    130 KiB artefact for text-akoma-normalize

What is deliberately mock / stub

  - gRPC wire from the client to a chain serve hub (Repository
    abstraction is in place; live impl is the next step)
  - NKR Bürokratiekosten-Datenbank ingestion (for the canonical
    h-Werte that close out the Engpass per Studie §6.7)
  - DESTATIS GENESIS-API adapter for stats.cohort_size

License: Apache-2.0. Author/contact in MACHBARKEITSSTUDIE.md.
Signed-off-by: flemming-it <sf@flemming.it>

flows/durchstich-gewo-14.yaml

@@ -0,0 +1,131 @@
+# Vertikaler Durchstich Phase 0 — eine Norm (GewO §14) durch
+# alle 8 law*-Schritte + Juristen-Approval + Audit.
+#
+# Voraussetzung:
+#   chain install text.akoma_normalize text.deontic_extract \
+#                 graph.citation_extract text.readability_score \
+#                 stats.cohort_size graph.shapley_attribution \
+#                 econ.skm_score law.benefit_score \
+#                 http.request system.approval
+#
+# Aufruf:
+#   chain run flows/durchstich-gewo-14.yaml \
+#     --input norm_url=https://www.gesetze-im-internet.de/gewo/__14.xml \
+#     --input cohort_id=berlin-kmu
+
+inputs:
+  norm_url:
+    type: string
+    required: true
+    description: ELI-resolvable URL der Quell-Norm
+  cohort_id:
+    type: string
+    required: true
+    description: Adressaten-Kohorte (siehe stats.cohort_size v0.1)
+  tariff_eur_per_hour:
+    type: number
+    default: 35.0
+    description: SKM-Tarif T
+
+outputs:
+  norm:        ${{ normalize.norm }}
+  duties:      ${{ duties.duties }}
+  citations:   ${{ citations.citations }}
+  cohort:      ${{ cohort.cohort }}
+  skm:         ${{ skm.report }}
+  frust:       ${{ frust.score }}
+  benefit:     ${{ benefit.score }}
+  attribution: ${{ attribution.attribution }}
+  reviewed:    ${{ review.decision == 'approve' }}
+
+steps:
+  - id: pull
+    use: http.request@^0
+    with:
+      url: ${{ inputs.norm_url }}
+      method: GET
+      etag_cache: true
+
+  - id: normalize
+    use: text.akoma_normalize@^0
+    with:
+      content: ${{ pull.body }}
+      mime: application/xml
+
+  - id: duties
+    use: text.deontic_extract@^0
+    with:
+      norm: ${{ normalize.norm }}
+
+  - id: citations
+    use: graph.citation_extract@^0
+    with:
+      norm: ${{ normalize.norm }}
+
+  - id: cohort
+    use: stats.cohort_size@^0
+    with:
+      cohort_id: ${{ inputs.cohort_id }}
+
+  # SKM-Aufbereitung: jede Duty bekommt P/F/T/h aus
+  # Kohorten-Größe + per-Duty-Heuristik (Phase 1: NKR-Datenbank).
+  # Hier inline aufgebaut; in Phase 1 wird das ein eigener
+  # `econ.duties_enrich`-Schritt.
+  - id: skm
+    use: econ.skm_score@^0
+    with:
+      duties:
+        duties:
+          - population: ${{ cohort.cohort.count }}
+            frequency: 1.0
+            tariff_eur_per_hour: ${{ inputs.tariff_eur_per_hour }}
+            time_hours_per_case: 0.5
+            source_norm: ${{ normalize.norm.eli }}
+            tier: ${{ cohort.cohort.tier }}
+
+  - id: frust
+    use: text.readability_score@^0
+    with:
+      norm:  ${{ normalize.norm }}
+      graph: ${{ citations.citations }}
+
+  - id: benefit
+    use: law.benefit_score@^0
+    with:
+      ratings:
+        schutz: 2.0
+        markt: 3.0
+        rechtssicherheit: 3.5
+        eu_binnenmarkt: 2.0
+        sicherheit: 1.5
+        umwelt: 0.0
+        einnahmen: 2.0
+        _sources:
+          schutz: NKR Stellungnahme zur GewO 2018
+          rechtssicherheit: IHK Berlin Mittelstandsumfrage 2024
+
+  # Attribution-Schritt mit Demo-Graph aus citations.
+  # Phase 1: graph.normalize baut den vollen Norm-Graph hier.
+  - id: attribution
+    use: graph.shapley_attribution@^0
+    with:
+      graph:
+        nodes:
+          - ${{ normalize.norm.eli }}
+          - eli/bund/gewo
+        edges:
+          - from: eli/bund/gewo
+            to:   ${{ normalize.norm.eli }}
+      target: ${{ normalize.norm.eli }}
+
+  # Juristen-Gate — Studie §3.3 macht das obligatorisch.
+  - id: review
+    use: system.approval@^0
+    with:
+      title: "F∆I Law-Heatmap — Review ${{ normalize.norm.eli }}"
+      payload:
+        norm:    ${{ normalize.norm }}
+        skm:     ${{ skm.report }}
+        benefit: ${{ benefit.score }}
+        frust:   ${{ frust.score }}
+        cohort:  ${{ cohort.cohort }}