feat(programs): Operational Knowledge — the transition is the unit + Transition Coverage KPI

Customers don't buy "EMV domain"; they buy "we have ISO 9001, help us with the CRA". The sellable
unit of knowledge is the TRANSITION (from -> to), not the law and not the capability. This reframes
the backlog from "model EMV next" to "the top demanded transitions". No new runtime framework (ADR-010).

- knowledge/programs/transitions.yaml: the Operational Knowledge backlog — the ~20-30 actually demanded
  transitions (of ~N*(N-1) possible) with priority. ISO27001->CRA, ISO9001->CRA, ISO9001->MaschinenVO
  (all 5-star), IEC62443->CRA, TISAX->CRA, ISO27001/IEC62443->NIS2, ISO14001->Umweltrecht.
- Transition Coverage KPI (reference suite, computed-not-stored): per transition a status DERIVED from
  the transition-pattern corpus (reviewed/validated/proven -> Gold, draft -> 🟡, none -> ⚪). Honest
  current state: ISO27001->CRA ✅ reviewed, ISO9001->CRA 🟡 draft, rest ⚪. Highest-priority gap =
  ISO9001->MaschinenVO (the next Track-B work) — a far stronger product indicator than "EMV 30% modelled".
- Three knowledge layers documented: Regulatory -> Operational (transitions/playbooks/deltas, the
  biggest differentiator) -> Verification (Vision V2). A domain is a TRANSITION PROGRAM with two tracks:
  Track A breadth (model sources, @Legal-KG/@Execution) + Track B product (transitions/playbooks/RTS
  per source, @Reasoning).
- ADR-010: the transition is the unit of knowledge; Transition Coverage KPI; three layers; two tracks.

10 program/transition-contract tests, check-loc 0. Knowledge data + ADR + reference harness =
non-runtime -> no deploy (ADR-001). No new module, no runtime change.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend-compliance/reference_scenarios/_helpers.py

@@ -155,8 +155,9 @@ def domain_programs_section(base_dir) -> None:
     idx = build_knowledge_index(_load("transition_patterns"), _load("implementation_playbooks"),
                                 _load("reference_transition_scenarios"))
     pdir = os.path.join(base_dir, "..", "knowledge", "programs")
-    progs = sorted((yaml.safe_load(open(os.path.join(pdir, f), encoding="utf-8"))
-                    for f in sorted(os.listdir(pdir)) if f.endswith(".yaml")), key=lambda p: p.get("backlog_rank", 99))
+    _all = [yaml.safe_load(open(os.path.join(pdir, f), encoding="utf-8"))
+            for f in sorted(os.listdir(pdir)) if f.endswith(".yaml")]
+    progs = sorted((p for p in _all if "backlog_rank" in p), key=lambda p: p["backlog_rank"])   # domain programs only
 
     _ALIAS = {"cyber resilience act": "cra", "maschinenverordnung": "maschinenvo", "iatf": "iatf16949"}
 
@@ -200,3 +201,65 @@ def domain_programs_section(base_dir) -> None:
         ("Reifegrad-KPI (computed-not-stored)", "PASS", "aus echtem Korpus abgeleitet (TP/PB/RTS je Domäne)"),
         ("Regelwerk-ID-Normalisierung", "TODO", "Alias CRA/MaschinenVO im KPI — kanonische IDs ausstehend"),
     ])
+
+
+def transition_coverage_section(base_dir) -> None:
+    """Transition Coverage — the TRANSITION is the unit of knowledge; status DERIVED from the corpus."""
+    import os
+    import yaml
+
+    kdir = os.path.join(base_dir, "..", "knowledge")
+    with open(os.path.join(kdir, "programs", "transitions.yaml"), encoding="utf-8") as h:
+        backlog = yaml.safe_load(h)
+    tpdir = os.path.join(kdir, "transition_patterns")
+    pats = []
+    for f in sorted(os.listdir(tpdir)):
+        if not f.endswith(".yaml"):
+            continue
+        d = yaml.safe_load(open(os.path.join(tpdir, f), encoding="utf-8"))
+        goal = d.get("transition_goal", {})
+        frm = goal.get("from", {}).get("standard", "")
+        to = goal.get("to")
+        tos = [it.get("regulation") or it.get("framework") or it.get("target")
+               for it in (to if isinstance(to, list) else [to]) if isinstance(it, dict)]
+        pats.append((frm, [t for t in tos if t], str(d.get("status", "draft"))))
+
+    _ALIAS = {"isoiec27001": "iso27001", "isoiec62443": "iec62443",
+              "cyberresilienceact": "cra", "maschinenverordnung": "maschinenvo"}
+
+    def _c(s):
+        k = "".join(ch for ch in str(s).lower() if ch.isalnum())
+        return _ALIAS.get(k, k)
+
+    _RANK = {"draft": 1, "reviewed": 2, "validated": 3, "proven": 4}
+    _ICON = {0: "⚪ nicht begonnen", 1: "🟡 Draft", 2: "✅ reviewed", 3: "✅ validated", 4: "✅ Gold"}
+
+    def _status(frm, to):
+        best = 0
+        for pf, ptos, st in pats:
+            if _c(pf) == _c(frm) and _c(to) in {_c(x) for x in ptos}:
+                best = max(best, _RANK.get(st, 1))
+        return best
+
+    w("## Transition Coverage — die Transition ist die Wissenseinheit (Operational Knowledge)")
+    w("")
+    w('_Der Kunde kauft nicht „EMV-Domain", sondern „wir haben ISO 9001 — helfen Sie uns beim CRA". Die Wissenseinheit ist die TRANSITION (nicht das Gesetz). Status je Transition aus dem echten Pattern-Korpus abgeleitet (computed-not-stored). Drei Ebenen: Regulatory → **Operational (hier, größter Differenzierer)** → Verification (Vision V2)._')
+    w("")
+    w("| Prio | Transition | Status |")
+    w("|---|---|---|")
+    rows = sorted(backlog["transitions"], key=lambda t: -t["priority"])
+    done = 0
+    for t in rows:
+        s = _status(t["from"], t["to"])
+        done += 1 if s else 0
+        w("| %s | `%s → %s` | %s |" % ("⭐" * t["priority"], t["from"], t["to"], _ICON[s]))
+    w("")
+    gaps = [t for t in rows if _status(t["from"], t["to"]) == 0]
+    if gaps:
+        w('**Größte Lücke (Track B als Nächstes):** `%s → %s` (%s) — höchstnachgefragte Transition OHNE Pattern. Stärkerer Produktindikator als „EMV 30%% modelliert".' % (gaps[0]["from"], gaps[0]["to"], "⭐" * gaps[0]["priority"]))
+    w("")
+    coverage_table([
+        ("Transition Coverage (Operational Knowledge)", "PASS", "%d von %d Top-Transitionen mit Pattern" % (done, len(rows))),
+        ("Wissenseinheit = Transition (nicht Gesetz)", "PASS", "verkauft wird der Übergang, z. B. ISO9001→CRA"),
+        ("3 Ebenen Regulatory→Operational→Verification", "PASS", "Operational = größter Differenzierer (ADR-010)"),
+    ])