update

backend/agents.py

@@ -49,7 +49,7 @@ def active_agents(scope_prefix: str | None = None) -> list[dict]:
 
 # Board-2-Calls tragen diese Marker im agent_key; alles andere unter blocks-{topic}- ist Board 1.
 _ARTEFAKT_MARKER = ("-art-gen", "-art-check", "-sb-enrich", "-sb-verify", "-sb-fix",
-                    "-sub-crossblock", "-outline")
+                    "-outline")
 
 
 def agent_ebene(key: str) -> str:

backend/auto_loop.py

@@ -17,23 +17,27 @@ async def auto_repair_loop(ebene: str, erst_note: float, reparieren, max_iter: i
     """Loop QA→Repair für eine Ebene.
 
     erst_note     : float — bereits gemessene QA-Note vor dem ersten Repair (0–10).
-    reparieren()  -> float: behebt die Befunde UND gibt die neu gemessene Note zurück
+    reparieren()  -> (float, bool): behebt die Befunde UND gibt die neu gemessene Note
-                    (die Repair-Bausteine messen ohnehin am Ende — keine Doppelmessung).
+                    zurück (die Repair-Bausteine messen ohnehin am Ende — keine Doppel-
+                    messung) plus „bewegt": ob die Runde etwas getan hat (Fixes, Merges,
+                    Freisprüche, Nach-Recherche). Eine bewegte Runde darf die Note auch
+                    mal transient senken (neue Blöcke → neue Verdachte) — Stillstand ist
+                    erst, wenn NICHTS mehr passiert UND die Note nicht steigt.
 
-    Stopp bei: Note == VOLL (fertig), Note verbessert sich nicht mehr (stillstand),
+    Stopp bei: Note == VOLL (fertig), unbewegt ohne Verbesserung (stillstand),
-    oder max_iter Runden (limit). Returns {ebene, note, runden, grund} mit
+    oder max_iter Runden (limit — begrenzt „bewegt ohne Notengewinn"-Livelocks).
-    grund ∈ {"fertig","stillstand","limit"} — der Aufrufer nutzt grund für die
+    Returns {ebene, note, runden, grund} mit grund ∈ {"fertig","stillstand","limit"}.
-    Fortschritts-/Systemfehler-Meldung.
     """
     if erst_note >= VOLL:
         return {"ebene": ebene, "note": erst_note, "runden": 0, "grund": "fertig"}
     note = erst_note
     for runde in range(1, max_iter + 1):
-        neu = await reparieren()
+        neu, bewegt = await reparieren()
-        log.info("[%s] Auto-Loop Runde %d: %.1f → %.1f", ebene, runde, note, neu)
+        log.info("[%s] Auto-Loop Runde %d: %.1f → %.1f (%s)",
+                 ebene, runde, note, neu, "bewegt" if bewegt else "unbewegt")
         if neu >= VOLL:
             return {"ebene": ebene, "note": neu, "runden": runde, "grund": "fertig"}
-        if neu <= note:  # keine Verbesserung ⇒ weitere Runden zwecklos (kein Repair-Pfad)
+        if not bewegt and neu <= note:  # nichts getan UND keine Verbesserung ⇒ kein Repair-Pfad
             return {"ebene": ebene, "note": neu, "runden": runde, "grund": "stillstand"}
-        note = neu
+        note = max(note, neu)
     return {"ebene": ebene, "note": note, "runden": max_iter, "grund": "limit"}

backend/blocks.py

@@ -370,27 +370,60 @@ def _pick_conversion(md: str | None, plain: str | None) -> tuple[str, str] | Non
     return plain, "pdftotext"
 
 
+# Small-Caps-/Math-Italic-Artefakte der PDF-Extraktion: LaTeX-\textsc/Kerning liest sich als
+# Binnen-Leerzeichen („H ITTING S ET", „N P") und erzeugt in der QA Phantom-Konzepte, die kein
+# Block je ankern kann. Regel A: Einzelgroßbuchstabe + GROSSLAUF(≥2) mergen — außer der Lauf
+# wird klein fortgesetzt („L NP-vollständig": L ist Variable, NP gehört zum Kompositum).
+_PDF_CAPS_SPLIT = re.compile(r"(?<![A-Za-zÄÖÜäöüß])([A-ZÄÖÜ]) ([A-ZÄÖÜ]{2,})(?!-?[a-zäöüß])")
+# Regel B: Einzelbuchstaben-PAAR („N P") — nur mergen, wenn das Ergebnis im selben Dokument
+# mehrfach ungespalten vorkommt (Frequenz-Beleg statt Domänenliste: „NP" ja, „C Y" nein).
+_PDF_LETTER_PAIR = re.compile(r"(?<![A-Za-zÄÖÜäöüß])([A-ZÄÖÜ]) ([A-ZÄÖÜ])(?![A-Za-zÄÖÜäöüß-])")
+_PDF_NORM_VERSION = 1  # bump → nächster Lauf re-konvertiert alle PDFs (Marker .pdf-txt-norm)
+
+
+def _entzerre_pdf_woerter(text: str) -> str:
+    """Gespaltene Wörter aus der PDF-Konvertierung zusammenfügen (nur Merges, kein Umbau).
+    Bewusste Restlücken: Zeilenumbruch-Splits und Mehrfach-Splits ohne Großlauf — dafür
+    sind Lücken-Research + Freispruch das Netz."""
+    prev = None
+    while prev != text:  # Ketten: „V ERTEX C OVER" braucht zwei Durchgänge pro Segment
+        prev = text
+        text = _PDF_CAPS_SPLIT.sub(r"\1\2", text)
+
+    def _belegt(m: re.Match) -> str:
+        merged = m.group(1) + m.group(2)
+        n = len(re.findall(rf"(?<![A-Za-zÄÖÜäöüß]){merged}(?![A-Za-zÄÖÜäöüß])", text))
+        return merged if n >= 3 else m.group(0)
+
+    return _PDF_LETTER_PAIR.sub(_belegt, text)
+
+
 def _convert_pdfs(project: Path) -> None:
     """Convert PDFs in the project to .txt — agents read text instead of page images.
 
     Called before every project generation; converts only if the .txt is missing or
     older than the PDF. Both converters run; the fidelity guard picks the better result
     per file. Neither available → hard error instead of an unreliable direct-read mode
-    (MiniMax image limit, vision cost)."""
+    (MiniMax image limit, vision cost). Ein Versions-Marker (.pdf-txt-norm) erzwingt nach
+    Änderungen an der Wort-Entzerrung einmalig die Re-Konvertierung trotz mtime-Cache."""
     pdfs = list(project.rglob("*.pdf"))
     if not pdfs:
         return
+    marker = project / ".pdf-txt-norm"
+    aktuell = marker.exists() and marker.read_text(encoding="utf-8").strip() == str(_PDF_NORM_VERSION)
     for pdf in pdfs:
         txt = pdf.with_suffix(".txt")
-        if txt.exists() and txt.stat().st_mtime >= pdf.stat().st_mtime:
+        if aktuell and txt.exists() and txt.stat().st_mtime >= pdf.stat().st_mtime:
             continue
         picked = _pick_conversion(_pdf_markdown(pdf), _pdf_plaintext(pdf))
         if picked is None:
             raise RuntimeError(f"PDF conversion failed ({pdf.name}): weder pymupdf4llm noch "
                                "pdftotext verfügbar/erfolgreich (pip install pymupdf4llm oder poppler-utils)")
         text, tool = picked
-        txt.write_text(text, encoding="utf-8")
+        txt.write_text(_entzerre_pdf_woerter(text), encoding="utf-8")
         _log(project.name, f"PDF konvertiert ({tool}): {pdf.name} → {txt.name}")
+    if not aktuell:
+        marker.write_text(str(_PDF_NORM_VERSION), encoding="utf-8")
 
 
 _SOURCE_TEMPLATE = {"projekt": "Blocks-Source-Projekt", "uni": "Blocks-Source-Uni", "link": "Blocks-Source-Link"}
@@ -1350,28 +1383,6 @@ def _completion_schema(data, n_umbrellas: int, ids: set[int]):
     return out
 
 
-# Deterministic backstop to the grouping judge's TEST 1 (type gate): an umbrella may bundle ONLY
-# constituent sub-definitions of ONE definition. If a member title carries a standalone-unit signal
-# (a named algorithm / problem / reduction / theorem), the umbrella is dissolved — those stay their own
-# blocks. Kept narrow so real definition-parts (Konfiguration, Übergangsfunktion δ, Literale, Makespan,
-# m Maschinen) never match; checked against the aak over-merge (member „Greedy-Algorithmus GA" hits).
-# Suffix-anchored head nouns (German compounds are head-final: „Approximations+algorithmus" has NO word
-# boundary before „algorithmus", so \bAlgorithmus\b misses it → the MAX-SAT over-merge). \w* absorbs the
-# modifier; the head noun stays the discriminator. FP-safe: no real TM/KNF definition-part ends in these
-# heads (Berechnung is deliberately NOT a head → „Akzeptierende Berechnung" stays a valid member).
-_GROUP_STANDALONE = re.compile(
-    r'\w*algorithm(?:us|en)\b|\w*problem(?:e|s|en)?\b|\w*reduktion(?:en)?\b|\bscheduling\b|[≤⪯]'
-    r'|^\s*(?:Satz|Lemma|Korollar|Theorem|Bemerkung|Beobachtung)\s*\d'
-    # atomicity: a named COMPLEXITY CLASS / a "…-Vollständigkeit(completeness)" / a "…Transformation" is a
-    # self-contained concept (learning-object / atomic-KC), never a sub-definition — a bundle of ≥1 such
-    # member is siblings, not one model → dissolve (catches the P/NP/NP-Vollständigkeit over-merge that NO
-    # cosine floor separates). Head-final compounds (\w*klasse absorbs "Komplexitäts+klasse"); FP-safe —
-    # no real TM/KNF/TSP/Scheduling definition-part carries these heads.
-    r'|\w*vollständigkeit\b|\w*completeness\b|\w*transformation(?:en)?\b|\w*klasse[nr]?\b', re.I)
-
-
-
-
 # --- Outline (blocks artifact: chapter structure, only read by the guide) ---
 
 def _outline_review_schema(data, valid: set[int], n_chapters: int, n_blocks: int):
@@ -1640,10 +1651,10 @@ async def _guide_ebene(topic: str, instructions: str, provider: str, is_cancelle
 
         async def _reparieren():
             set_p("Befunde beheben (Guide)…")
-            await guide_board.repair_karten(topic, fmt)          # befundtragende Karten → pruefer
+            betroffen = await guide_board.repair_karten(topic, fmt)  # Karten → pruefer/fix
             await guide.generate_guide(topic=topic, format_name=fmt, guide_id=guide_id,
                                        instructions=instructions, provider=provider)  # resumt offene Karten
-            return await _messen()
+            return await _messen(), len(betroffen) > 0
 
         res = await auto_repair_loop("Guide", erst, _reparieren)
         if res["grund"] != "fertig":

backend/board_artefacts.py

@@ -4,27 +4,23 @@ A card is spawned by board 1's `done` column per mirrored block and runs through
   generate → verify (inkl. Fix-Tail) → artefakte (Gen + Prüfer) → finalize
 (die verschmolzenen Calls liegen in block_calls.py — 4–5 serielle Segmente statt ~20).
 finalize (SERIAL) merges the block's results into the global sidecar/facts/pattern/artefakte
-files + the DB tables. Danach zwei topic-weite BARRIEREN: `konsolidierung` (cross-block
+files + the DB tables. Danach eine topic-weite BARRIERE: `outline` (prerequisite graph →
-sub dedup, faltet per repair.falte_sub) und `outline` (prerequisite graph → chapter order),
+chapter order), re-run once per generation run."""
-re-run once per generation run — outline läuft parallel zur Dedup-Barriere."""
 
 import asyncio
-import hashlib
 import json
 import logging
 import re
 
 import database as db
 import blocks
-import embedding
 from block_calls import _artefakte_block, _generate_block, _verify_block
-from blocks import ARTEFACT_TYPES, _match_sub, _neg_set, _sink_json, _outline_block
+from blocks import ARTEFACT_TYPES, _match_sub, _outline_block
-from config import CROSS_CHUNK_PAARE, EMBEDDING_AKTIV, SUB_DUP_KANDIDAT_COS
 from fsutil import atomic_write_json
 from jsonio import read_json_file as _json_file
 from kanban import Flow, Stage
-from pipeline import FAILED, GenContext, _extra, _log, _prompt, _timeout, run_single_slot
+from pipeline import GenContext, _log
-from textkit import _norm_title, _title, parse_facts
+from textkit import _norm_title, _title
 
 log = logging.getLogger("creator.board_artefacts")
 
@@ -274,162 +270,6 @@ async def _proc_artefakte(ctx: GenContext, flow: Flow, files: dict, instructions
     await _gather_cards(ctx, flow, cards, one)
 
 
-def _cross_schema(data) -> dict[int, str] | None:
-    """{"pairs": {"1": "a"|"b"|"nein"}} → {pair_nr: verdict} · otherwise None."""
-    if not isinstance(data, dict) or not isinstance(data.get("pairs"), dict):
-        return None
-    out: dict[int, str] = {}
-    for k, v in data["pairs"].items():
-        try:
-            nr = int(k)
-        except (ValueError, TypeError):
-            continue
-        s = str(v).strip().casefold()
-        if s in ("a", "b", "nein"):
-            out[nr] = s
-    return out or None
-
-
-async def _proc_konsolidierung(ctx: GenContext, flow: Flow, files: dict, instructions: str, cards):
-    """BARRIER/drain am RUN-ENDE — cross-block sub dedup: the SAME statement carried by two
-    blocks (measured on Markdown: tab handling in 3 blocks, HTML blocks, backslash escapes —
-    the in-block paths never see these). Embedding candidates (block≠block, cos ≥
-    SUB_DUP_KANDIDAT_COS) go to a two-judge panel; UNANIMITY decides which block keeps the
-    statement. Sitzt seit dem Umbau NACH finalize: als Mittel-Barriere wartete jede fertige
-    Karte auf die langsamste (gemessen: 8:46 min Leerlauf pro Block, kanban-smoke). Der
-    Verlierer wird per repair.falte_sub gefaltet (variant + Fragen/Artefakte umhängen) —
-    die wenigen Cross-Dubletten kosten so ein paar umsonst generierte Artefakte statt
-    Minuten Wandzeit für alle. Fail-open on judge failure/dissent."""
-    from repair import falte_sub
-    topic = flow.topic
-    work_dir = flow.work_dir
-    # Resume-Karten aus der alten Stage-Position (Barriere lag vor den Fragen): erst fertig
-    # generieren — die Barriere feuert erneut, wenn alle wieder hier sind. Direkt dedupen
-    # ginge schief: finalize würde den gefalteten Sub aus dem Karten-Sidecar re-spiegeln.
-    nachzuegler = [(c["card_id"], "artefakte" if "sidecar" in c["payload"] else "generate")
-                   for c in cards if "pattern" not in c["payload"]]
-    if nachzuegler:
-        await db.kanban_advance_many(topic, BOARD, nachzuegler)
-        flow.wake.set()
-        return
-
-    async def _advance_all():
-        await db.kanban_advance_many(topic, BOARD, [(c["card_id"], DONE) for c in cards])
-        flow.wake.set()
-
-    rows = [r for r in await db.list_subblocks(topic) if r["status"] == "consensus"]
-    if len(rows) < 2 or not EMBEDDING_AKTIV or not await asyncio.to_thread(embedding.available):
-        await _advance_all()
-        return
-    sims = await asyncio.to_thread(embedding.embed_sims, [r["sub_title"] for r in rows])
-    if sims is None:
-        await _advance_all()
-        return
-    negs = [_neg_set(r["sub_title"]) for r in rows]
-    pairs = [(i, j) for i in range(len(rows)) for j in range(i + 1, len(rows))
-             if rows[i]["block_norm"] != rows[j]["block_norm"] and negs[i] == negs[j]
-             and float(sims[i][j]) >= SUB_DUP_KANDIDAT_COS]
-    if not pairs:
-        await _advance_all()
-        return
-
-    def _kp(r: dict) -> list:
-        return parse_facts(r.get("facts")).get("key_points") or []
-
-    def _side(tag: str, r: dict) -> str:
-        return f"{tag}: [Block: {r['block']}] {r['sub_title']}" + "".join(f"\n   - {p}" for p in _kp(r))
-
-    # chunked judging: ONE call over all pairs scaled its timeout past 50 min, and a hung
-    # call blocked the barrier for the full window (measured on aak: 196 pairs, 2×54 min)
-    chunks = [pairs[lo:lo + CROSS_CHUNK_PAARE] for lo in range(0, len(pairs), CROSS_CHUNK_PAARE)]
-
-    async def _urteile_chunk(chunk: list[tuple[int, int]]) -> dict[int, str]:
-        """Two judges (+ substitute, + tie-breaker) over one pair chunk → {local_k: verdict};
-        empty dict = fail-open (pairs stay)."""
-        lines = "\n\n".join(
-            f"{k}.\n{_side('A', rows[i])}\n{_side('B', rows[j])}"
-            for k, (i, j) in enumerate(chunk, 1))
-        h = hashlib.md5(lines.encode()).hexdigest()[:8]
-        paths = [work_dir / f"sub-crossblock-{h}-j{j}.json" for j in (1, 2)]
-
-        async def _judge(j, path, plines, n):
-            if _cross_schema(_json_file(path)) is not None:
-                return  # resume
-            status, _v = await run_single_slot(
-                ctx, f"Sub-Crossblock j{j}", key=f"blocks-{topic}-sub-crossblock-{h}-j{j}",
-                prompt=_prompt("Subblock-Crossblock", topic=topic, pairs=plines, extra=_extra(instructions)),
-                role="judge", capabilities="none",
-                payload=lambda result, p=path: _sink_json(result, p, _cross_schema),
-                timeout=_timeout("subblock_check", n))
-            if status == FAILED:
-                _log(topic, f"Sub-Crossblock j{j} ohne Ergebnis — fail-open")
-
-        await asyncio.gather(*[_judge(j, p, lines, len(chunk)) for j, p in zip((1, 2), paths)])
-        if ctx.is_cancelled():
-            return {}
-        outs = [o for p in paths if (o := _cross_schema(_json_file(p))) is not None]
-        if len(outs) == 1:  # Ersatz-Richter statt fail-open bei EINEM Ausfall
-            ersatz = work_dir / f"sub-crossblock-{h}-jE.json"
-            await _judge("E", ersatz, lines, len(chunk))
-            if ctx.is_cancelled():
-                return {}
-            outs = [o for p in [*paths, ersatz] if (o := _cross_schema(_json_file(p))) is not None]
-        if len(outs) != 2:
-            if outs:
-                _log(topic, "Sub-Crossblock: nur 1/2 Richter — fail-open")
-            return {}
-        final = {k: (outs[0].get(k, "nein") if outs[0].get(k, "nein") == outs[1].get(k, "nein")
-                     else "uneinig") for k in range(1, len(chunk) + 1)}
-        disputed = [k for k, v in final.items() if v == "uneinig"]
-        if disputed:  # tie-breaker: a third judge sees ONLY the disputed pairs, majority 2/3
-            d_lines = "\n\n".join(
-                f"{x}.\n{_side('A', rows[chunk[k - 1][0]])}\n{_side('B', rows[chunk[k - 1][1]])}"
-                for x, k in enumerate(disputed, 1))
-            p3 = work_dir / f"sub-crossblock-{h}-j3.json"
-            await _judge(3, p3, d_lines, len(disputed))
-            if ctx.is_cancelled():
-                return {}
-            v3 = _cross_schema(_json_file(p3)) or {}
-            if not v3:
-                _log(topic, "Sub-Crossblock j3 ohne Ergebnis — strittige Paare bleiben")
-            for x, k in enumerate(disputed, 1):
-                t = v3.get(x, "nein")
-                if t in (outs[0].get(k, "nein"), outs[1].get(k, "nein")):
-                    final[k] = t  # majority 2/3; anything else stays disputed → no fold
-        return final
-
-    chunk_finals = await asyncio.gather(*[_urteile_chunk(c) for c in chunks])
-    if ctx.is_cancelled():
-        return
-    final_all: dict[int, str] = {}  # global pair index (1-based over `pairs`) → verdict
-    for cnr, fin in enumerate(chunk_finals):
-        for k, v in fin.items():
-            final_all[cnr * CROSS_CHUNK_PAARE + k] = v
-    journal = {"paare": len(pairs), "chunks": len(chunks), "gefaltet": [], "verdicts": []}
-    gone: set[tuple] = set()
-    for k, (i, j) in enumerate(pairs, 1):
-        verdict = final_all.get(k, "nein")
-        journal["verdicts"].append({"a": f"{rows[i]['block']} · {rows[i]['sub_title']}",
-                                    "b": f"{rows[j]['block']} · {rows[j]['sub_title']}",
-                                    "verdict": verdict})
-        if verdict not in ("a", "b"):
-            continue
-        win, lose = (rows[i], rows[j]) if verdict == "a" else (rows[j], rows[i])
-        wk = (win["block_norm"], win["sub_norm"])
-        lk = (lose["block_norm"], lose["sub_norm"])
-        if lk in gone or wk in gone:  # keeper already folded → don't chain away the content
-            continue
-        await falte_sub(topic, files, win, lose)
-        gone.add(lk)
-        journal["gefaltet"].append({"weg": f"{lose['block']} · {lose['sub_title']}",
-                                    "bleibt": f"{win['block']} · {win['sub_title']}"})
-    if journal["gefaltet"]:
-        _log(topic, f"Sub-Crossblock: {len(journal['gefaltet'])} blockübergreifende Dublette(n) gefaltet")
-    hg = hashlib.md5("\n".join(f"{i}:{j}" for i, j in pairs).encode()).hexdigest()[:8]
-    atomic_write_json(work_dir / f"sub-crossblock-{hg}.json", journal, indent=1)
-    await _advance_all()
-
-
 # ── Finalize (SERIAL): merge into the global files + DB tables ─────────────────────
 def _merge_json(path, block_keys: dict) -> None:
     data = _json_file(path)

backend/board_inventory.py

@@ -39,7 +39,7 @@ import kanban
 from kanban import Flow, Stage, chain_stages
 import blocks
 from blocks import (
-    _FILTER_NOTATION, _GROUP_STANDALONE,
+    _FILTER_NOTATION,
     _build_research_prompt, _canonical, _canonical_key, _chunk_nums, _cliques,
     _completion_schema, _containment_parent, _crawl_index, _file_payload,
     _filter_schema, _filter_suspect, _is_artifact, _is_named_statement,
@@ -47,13 +47,13 @@ from blocks import (
     _direction_conflict, _relation_conflict, _root, _supplement_schema, _text_sections, _umbrella_schema,
     _aspect_marker, _title_variants, _corpus_files, _evidence_pack, _sink_json, source_folder,
 )
-from config import (QA_GATE_NOTE, QA_GATE_LLM,
+from config import (QA_GATE_NOTE, QA_GATE_LLM, LUECKEN_RESEARCH_MAX,
     DEDUP_GLOBAL_FLOOR, DEDUP_PAIR_FLOOR, DEDUP_PAIRS_CHUNK, DEDUP_TITLE_AUTO, FILTER_CHUNK,
     FILTER_RECHECK_PANEL, CONSOLIDATION_PANEL, RESEARCH_BATCH, RESEARCH_READERS,
     RESEARCH_THEMA_AGENTS,
     BLOCKS_GRUPPIERUNG_AKTIV, EMBEDDING_AKTIV, EMBEDDING_BLOCK_CAP,
     EMBEDDING_SIBLING_CAP, EMBEDDING_SIBLING_FLOOR, FRAGMENT_MIN_COS,
-    GROUP_MIN_COS_FLOOR, GROUP_RECONCILE_FLOOR,
+    GROUP_RECONCILE_FLOOR, GROUP_THEMES_PER_SQRT,
 )
 from fsutil import atomic_write_json, atomic_write_text
 from jsonio import read_json_file as _json_file
@@ -1272,6 +1272,15 @@ async def _proc_dedup(ctx: GenContext, flow: Flow, cards):
     flow.wake.set()
 
 
+def _themen_zielband(n: int) -> tuple[int, int]:
+    """Weiches Prompt-Band der Themenzahl: k = GROUP_THEMES_PER_SQRT·√n, ±30 %, min 2.
+    n ist die Item-Zahl der GROUPING-WELLE — die Supplement-Welle bekommt bewusst ein
+    kleines Band aus ihrem kleinen n (sie sortiert nur Neuzugänge nach)."""
+    k = GROUP_THEMES_PER_SQRT * math.sqrt(max(n, 1))
+    lo = max(2, math.floor(0.7 * k))
+    return lo, max(lo + 1, math.ceil(1.3 * k))
+
+
 async def _proc_grouping(ctx: GenContext, flow: Flow, cards):
     """BARRIER/drain — umbrella grouping over the filter survivors: embedding sibling clusters
     (low floor, high recall) + top-down pass, one judge per cluster, type gate + min-cos backstop,
@@ -1300,11 +1309,7 @@ async def _proc_grouping(ctx: GenContext, flow: Flow, cards):
     all_ids = set(range(1, n + 1))
     full_list = "\n".join(f"{i}. {texts[i - 1]}" for i in range(1, n + 1))
     h = _h(*[r["card_id"] for r in rows])
-
+    theme_lo, theme_hi = _themen_zielband(n)
-    def _min_cos(idxs):
-        if len(idxs) < 2:
-            return 1.0
-        return round(min(float(sims[i][j]) for a, i in enumerate(idxs) for j in idxs[a + 1:]), 3)
 
     async def _assess(tag, cand_text, count):
         path = work_dir / f"gruppierung-{h}-c{tag}.json"
@@ -1312,7 +1317,8 @@ async def _proc_grouping(ctx: GenContext, flow: Flow, cards):
             status, _v = await run_single_slot(
                 ctx, f"Gruppierung {tag}", key=f"blocks-{topic}-gruppierung-{h}-c{tag}",
                 prompt=_prompt("Blocks-Gruppierung", topic=topic, candidates=cand_text,
-                               list=full_list, out_path=path),
+                               list=full_list, out_path=path,
+                               theme_lo=theme_lo, theme_hi=theme_hi, n_items=n),
                 role="judge", capabilities="files",
                 payload=lambda result, p=path: _umbrella_schema(_json_file(p), all_ids),
                 timeout=_timeout("research_mapping", count))
@@ -1349,7 +1355,6 @@ async def _proc_grouping(ctx: GenContext, flow: Flow, cards):
             # Bottom-up card-sorting: keine type-gate/min-cos-Vetos mehr — jedes Item soll in
             # ein Thema; ein „Fehl-Merge" ist billig (Item bleibt als Sub erhalten, keine Lücke).
             mrows = [rows[m - 1] for m in members]
-            mc = _min_cos([m - 1 for m in members])
             unorm = _norm_title(title)
             member_norms = {r["title_norm"] for r in mrows}
             if unorm not in member_norms and unorm in seen_norm:
@@ -1358,7 +1363,7 @@ async def _proc_grouping(ctx: GenContext, flow: Flow, cards):
                 continue
             used.update(members)
             seen_norm.add(unorm)
-            chosen.append({"umbrella": title, "description": desc, "min_cos": mc, "members": members})
+            chosen.append({"umbrella": title, "description": desc, "members": members})
     # reconcile: same parent proposed twice under different titles → union
     if len(chosen) >= 2:
         uv = await _vec_rows(flow, [f"{c['umbrella']} — {c['description']}" for c in chosen])
@@ -1462,24 +1467,25 @@ async def _proc_gap_check(ctx: GenContext, flow: Flow, cards):
     flow.wake.set()
 
 
-async def _supplement_beleg(ctx: GenContext, flow: Flow, supplements: list) -> list:
+async def _supplement_beleg(ctx: GenContext, flow: Flow, supplements: list, tag: str = "") -> list:
     """Evidence gate for supplement proposals: keyword excerpts per proposal, ONE no-tool
     judge marks material coverage (ja/nein). Proposals without any matching excerpt drop
-    immediately; a failed gate keeps nothing (creep is costlier than a lost bonus round)."""
+    immediately; a failed gate keeps nothing (creep is costlier than a lost bonus round).
+    `tag` trennt Resume-Datei/Key je Aufrufer (Lücken-Recherche läuft mehrere Runden)."""
     topic = flow.topic
     folder = source_folder(topic)
     packs = [(t, d, _evidence_pack(folder, None, [t], budget=6000)) for t, d in supplements]
     cands = [(t, d, ev) for t, d, ev in packs if ev]
     kept: list = []
     if cands:
-        path = flow.work_dir / "supplement-beleg.json"
+        path = flow.work_dir / f"supplement-beleg{tag}.json"
         ids = set(range(1, len(cands) + 1))
         verdict = _yesno_schema(_json_file(path), ids)
         if verdict is None:
             lines = "\n\n".join(f"{k}. {t} — {d}\nAUSZÜGE:\n{ev}"
                                 for k, (t, d, ev) in enumerate(cands, 1))
             status, verdict = await run_single_slot(
-                ctx, "Supplement-Beleg", key=f"blocks-{topic}-supplement-beleg",
+                ctx, "Supplement-Beleg", key=f"blocks-{topic}-supplement-beleg{tag}",
                 prompt=_prompt("Blocks-Supplement-Beleg", topic=topic, proposals=lines,
                                extra=_extra(flow.state.get("instructions", ""))),
                 role="judge", capabilities="none",
@@ -1525,11 +1531,21 @@ async def _supplement_producer(ctx: GenContext, flow: Flow, titles: list[str]):
     # treats). Only proposals the material itself covers may enter the inventory.
     if supplements and source_folder(topic):
         supplements = await _supplement_beleg(ctx, flow, supplements)
-    # Dead lineage: blocks demoted by the fragment filter (and their cluster + title cards)
+    new, reopened = await _ingest_proposals(topic, supplements or [])
-    # must NOT dedup a supplement proposal — their content is gone. A hit on a dead title
+    if new or reopened:
-    # REOPENS the lineage instead: the title card rejoins its cluster (live re-cluster) and
+        _log(topic, f"Supplement: {new} Block-Kandidat(en) → ingest, {reopened} wiedereröffnet")
-    # the respawned block gets a fresh fragment_filter pass. failed-quorum/pre-reject stay
+        flow.wake.set()
-    # in the dedup: those were rejected as non-blocks, not lost as content.
+
+
+async def _ingest_proposals(topic: str, supplements: list) -> tuple[int, int]:
+    """Vorschläge (title, description) als Titel-Karten einspeisen — gemeinsamer Ingest-
+    Schwanz von Supplement- und Lücken-Recherche. → (neu, wiedereröffnet).
+
+    Dead lineage: blocks demoted by the fragment filter (and their cluster + title cards)
+    must NOT dedup a proposal — their content is gone. A hit on a dead title REOPENS the
+    lineage instead: the title card rejoins its cluster (live re-cluster) and the respawned
+    block gets a fresh fragment_filter pass. failed-quorum/pre-reject stay in the dedup:
+    those were rejected as non-blocks, not lost as content."""
     dead_reasons = {"fragment", "drop-collateral", "drop"}
     cards = await db.kanban_cards(topic, board=BOARD)
     dead_clusters = {c["payload"].get("cluster") for c in cards
@@ -1563,7 +1579,7 @@ async def _supplement_producer(ctx: GenContext, flow: Flow, titles: list[str]):
         if (k := _canonical_key(tt)):
             known_keys.add(k)
     new = reopened = 0
-    for t, d in (supplements or []):
+    for t, d in supplements:
         t, d = clean_title(t), clean_title(d)
         norm = _norm_title(t)
         key = _canonical_key(t)
@@ -1587,9 +1603,57 @@ async def _supplement_producer(ctx: GenContext, flow: Flow, titles: list[str]):
             card["payload"]["supplement"] = True
             await db.kanban_set_payload(topic, BOARD, norm, card["payload"])
         new += 1
-    if new or reopened:
+    return new, reopened
-        _log(topic, f"Supplement: {new} Block-Kandidat(en) → ingest, {reopened} wiedereröffnet")
+
-        flow.wake.set()
+
+async def _luecken_producer(ctx: GenContext, flow: Flow, report: dict) -> int:
+    """Gezielte Nach-Recherche für offene QA-Lücken (Auto-Loop): EIN Agent sieht Bestand
+    plus Lücken-Fundstellen (Abschnittstexte deterministisch re-extrahiert, gleicher
+    Splitter wie die QA) und schlägt NUR dafür Blöcke vor — leere Liste erlaubt.
+    Danach Evidence-Gate + Ingest wie beim Supplement; neue Titel durchlaufen alle
+    Inventar-Gates bis done_block. → Zahl neuer/wiedereröffneter Karten."""
+    import qa as _qa
+    topic = flow.topic
+    lk, kl = _qa.offene_luecken(report)
+    if not (lk or kl):
+        return 0
+    flow.add_producer()  # Engine am Leben halten, solange der Research-Call läuft
+    try:
+        texts = _qa._corpus_texts(topic)
+        sections = {f: _qa._sections(t) for f, t in texts.items()}
+        gaps = []
+        for x in lk[:20]:
+            sec = sections.get(x.get("datei"), [])
+            k = int(x.get("abschnitt") or 0)
+            volltext = sec[k - 1][:1500] if 0 < k <= len(sec) else x.get("vorschau", "")
+            gaps.append(f"[{x.get('datei')} #{k}]\n{volltext}")
+        gaps += [f"NAMED RESULT (no covering block): {n}" for n in kl[:20]]
+        done = await db.kanban_cards(topic, board=BOARD, kind="block", stage="done_block")
+        runde = flow.state.get("luecken_runde", 0)
+        path = flow.work_dir / f"luecken-research-r{runde}.json"
+        supplements = _supplement_schema(_json_file(path))
+        if supplements is None:
+            status, supplements = await run_single_slot(
+                ctx, f"Lücken-Recherche r{runde}", key=f"blocks-{topic}-luecken-nachfass-r{runde}",
+                prompt=_prompt("Blocks-Luecken-Research", topic=topic,
+                               blocks="\n".join(f"- {c['payload'].get('title', '')}" for c in done),
+                               gaps="\n\n".join(gaps), out_path=path,
+                               extra=_extra(flow.state.get("instructions", ""))),
+                role="quick", capabilities="files",
+                payload=lambda result, p=path: _supplement_schema(_json_file(p)),
+                timeout=_timeout("ergaenzung"))
+            if status != OK or supplements is None:
+                _log(topic, "Lücken-Recherche ohne Ergebnis — übersprungen")
+                return 0
+        if supplements and source_folder(topic):
+            supplements = await _supplement_beleg(ctx, flow, supplements, tag=f"-l{runde}")
+        new, reopened = await _ingest_proposals(topic, supplements or [])
+        if new or reopened:
+            _log(topic, f"Lücken-Recherche: {new} Kandidat(en) → ingest, {reopened} wiedereröffnet")
+            flow.wake.set()
+        return new + reopened
+    finally:
+        flow.done_producer()
 
 
 async def _proc_done(ctx: GenContext, flow: Flow, cards):
@@ -1731,11 +1795,11 @@ async def run_boards(ctx: GenContext, set_p, files: dict, q: dict, folder, instr
     stages = chain_stages(stages)
     if artefacts:
         # Outline needs every block's TITLE + FACTS (aus generate), nothing later: cut the
-        # post-generate stages from its barrier so it runs parallel to verify…finalize AND
+        # post-generate stages from its barrier so it runs parallel to verify…finalize
-        # zur Cross-Dedup-Barriere des langsamsten Blocks (makespan tail).
+        # des langsamsten Blocks (makespan tail).
         outline = next(s for s in stages if s.stage == "outline")
         outline.upstream = [u for u in outline.upstream if u not in
-                            ("verify", "artefakte", "finalize", "konsolidierung")]
+                            ("verify", "artefakte", "finalize")]
     producers = _build_producers(ctx, flow, q, folder, instructions) if (research and inventory) else []
 
     async def _as_producer(coro):
@@ -1792,17 +1856,24 @@ async def run_boards(ctx: GenContext, set_p, files: dict, q: dict, folder, instr
 _QA_GATE_POLL = 2.0  # Sekunden zwischen Quiescence-Checks des QA-Wächters
 
 
+async def _warte_inventar_ruhe(flow: Flow, inv_names: list[str]) -> None:
+    """Bis das Inventar quiescent ist (Research fertig, keine aktiven Karten in den
+    Inventar-Stages) oder der Flow stoppt — Poll-Kopf des QA-Wächters, auch nach
+    Lücken-Recherche-Runden gebraucht (neue Karten laufen erst durch alle Gates)."""
+    while not flow.stop:
+        if (flow.research_done and not flow.active_in(inv_names)
+                and await db.kanban_count(flow.topic, inv_names) == 0):
+            return
+        await asyncio.sleep(_QA_GATE_POLL)
+
+
 async def _qa_gate_watch(ctx: GenContext, flow: Flow, inv_names: list[str], set_p):
     """Companion task: once the inventory is quiescent, run the QA once and decide —
     open the board-2 gate or pause the flow. Fail-OPEN on errors (QA is a helper,
     not a jailer); qa_force short-circuits to open."""
     topic = flow.topic
     try:
-        while not flow.stop:
+        await _warte_inventar_ruhe(flow, inv_names)
-            if (flow.research_done and not flow.active_in(inv_names)
-                    and await db.kanban_count(topic, inv_names) == 0):
-                break
-            await asyncio.sleep(_QA_GATE_POLL)
         if flow.stop or ctx.is_cancelled():
             return
         if flow.state.get("qa_force"):
@@ -1832,16 +1903,33 @@ async def _qa_gate_watch(ctx: GenContext, flow: Flow, inv_names: list[str], set_
             flow.wake.set()
             return
 
-        # Auto an: „Befunde beheben"-Loop bis 100 % / Stillstand / 10×.
+        # Auto an: „Befunde beheben"-Loop bis 100 % / Stillstand / 10×. Offene Lücken
+        # bekommen erst bis zu LUECKEN_RESEARCH_MAX gezielte Nach-Recherche-Runden;
+        # das Lücken-Urteil (Freispruch/bestätigt) fällt erst, wenn die Recherche
+        # nichts mehr bewegt — sonst würde eine füllbare Lücke vorschnell verurteilt.
         from auto_loop import auto_repair_loop
         import repair as _repair
 
         async def _reparieren():
+            rep = qa.latest_report(topic) or {}
+            research_bewegt = False
+            runde = flow.state.get("luecken_runde", 0)
+            lk, kl = qa.offene_luecken(rep)
+            if (lk or kl) and runde < LUECKEN_RESEARCH_MAX:
+                flow.state["luecken_runde"] = runde + 1
+                set_p(f"Lücken-Recherche {runde + 1}/{LUECKEN_RESEARCH_MAX}…")
+                neue = await _luecken_producer(ctx, flow, rep)
+                research_bewegt = neue > 0
+                if neue:  # neue Titel durchlaufen alle Gates — erst Ruhe, dann messen
+                    await _warte_inventar_ruhe(flow, inv_names)
+            if flow.stop or ctx.is_cancelled():
+                return float(flow.state.get("qa_note") or 0.0), False
             set_p("Befunde beheben (Inventar)…")
-            r = await _repair.repair_befunde(topic, "inventory")  # behebt + misst neu
+            r = await _repair.repair_befunde(topic, "inventory",
+                                             luecken_urteil=not research_bewegt)
             n = float(r.get("note", 10.0))
             flow.state["qa_note"] = n
-            return n
+            return n, bool(r.get("aktionen", 0)) or research_bewegt
 
         res = await auto_repair_loop("Inventar", note, _reparieren)
         end_note = res["note"]
@@ -1899,7 +1987,7 @@ async def _artefakt_auto_loop(ctx: GenContext, flow: Flow, set_p):
         async def _reparieren():
             set_p("Befunde beheben (Artefakte)…")
             r = await _repair.repair_befunde(topic, "artefacts")
-            return float(r.get("note_artefakte") or 10.0)
+            return float(r.get("note_artefakte") or 10.0), bool(r.get("aktionen", 0))
 
         res = await auto_repair_loop("Artefakte", na, _reparieren)
         flow.state["note_artefakte"] = res["note"]
@@ -1986,7 +2074,6 @@ COLUMNS = [
     ("artefacts", "verify", "Prüfen", "ablock"),
     ("artefacts", "artefakte", "Lernmittel", "ablock"),
     ("artefacts", "finalize", "Zusammenführen", "ablock"),
-    ("artefacts", "konsolidierung", "Konsolidierung", "ablock"),
     ("artefacts", "outline", "Gliederung", "outline"),
     ("artefacts", "done_artefact", "Fertig", "ablock"),
 ]
@@ -2053,13 +2140,15 @@ async def board_snapshot(topic: str, limit: int = 20) -> dict:
 
 def _qa_view(topic: str, counts: dict, flow) -> dict | None:
     """Latest QA report digest for the board header. `pausiert` = the gate stopped the
-    flow (score below threshold, board-2 cards waiting, no flow running)."""
+    flow (score below 100 %, board-2 cards waiting, no flow running) — das Auto-Gate
+    öffnet nur bei VOLL; eine 9.6 pausierte den Loop, galt hier aber nicht als pausiert."""
     # no inventory (deleted/never built) → no badge; the report files stay on purpose,
     # so the first run after a rebuild diffs against the old state
     if not counts.get("inventory", {}).get("done_block", 0) and not (
             flow and flow.state.get("qa_note") is not None):
         return None
     import qa
+    from auto_loop import VOLL
     r = qa.latest_report(topic)
     if r is None:
         return None
@@ -2067,9 +2156,9 @@ def _qa_view(topic: str, counts: dict, flow) -> dict | None:
     if note is None:
         return None
     wartend = counts.get("artefacts", {}).get("generate", 0)
-    pausiert = bool(note < QA_GATE_NOTE and wartend and flow is None)
+    pausiert = bool(note < VOLL and wartend and flow is None)
     return {"note": note, "note_artefakte": r.get("note_artefakte"),
-            "schwelle": QA_GATE_NOTE, "pausiert": pausiert,
+            "schwelle": VOLL, "pausiert": pausiert,
             "quoten": r.get("quoten", {}),
             "befunde": (r.get("fremd", []) + r.get("unecht", []))[:6]}
 

backend/config.py

@@ -75,9 +75,6 @@ SEED_COVER_COS = 0.80
 # (Markdown: 50 pairs in the band, 4 above) — below every auto-merge threshold, so an LLM
 # judge decides. Candidates only; a merge still needs judge unanimity.
 SUB_DUP_KANDIDAT_COS = 0.75
-# Cross-block judge pairs per call: ONE call over all pairs scaled its timeout to 54 min
-# and a hung call blocked the barrier that long (aak: 196 pairs) — chunks cap it at ~15 min.
-CROSS_CHUNK_PAARE = 40
 
 # Umbrella grouping (block granularity level 2, step "Blocks-Gruppierung", AFTER the filter):
 # collapse sibling DEFINITIONS that are components of ONE umbrella concept (TM model:
@@ -94,16 +91,13 @@ EMBEDDING_SIBLING_CAP = 18       # a rich model (TM) can have many constituent p
 # titles (e.g. two „Turingmaschine"-umbrellas). Merge umbrella pairs whose title+description cosine is
 # ≥ this (conservative → only true same-parent duplicates, never two distinct umbrellas).
 GROUP_RECONCILE_FLOOR = 0.75
-# Over-merge backstop ONLY (no-structure floor). Research (meronymy ≠ similarity): parts of ONE model are
+# Zielband der Themen-Blockzahl im Gruppierungs-Prompt: k = GROUP_THEMES_PER_SQRT·√n
-# legitimately DISSIMILAR (TM: Alphabet/Konfiguration/δ ~0.22), while distinct same-type concepts (P/NP/…)
+# (n = Items der Grouping-Welle), Band [0.7k, 1.3k] — weiche Vorgabe, kein Cap. √n hält
-# are SIMILAR (~0.85) — so member-vs-member cosine is the WRONG instrument for over-merge (empirically
+# Blockzahl UND mittlere Blockgröße sublinear (n=30 → ~4–8, n=285 → ~12–22; das alte
-# inverted: TM 0.218 < the P/NP bundle 0.227). The real precision floor is the ATOMICITY type-guard
+# statische „15–25" passte implizit nur zu n≈225–625).
-# (_GROUP_STANDALONE: a member that is a named algorithm/problem/theorem/complexity-class dissolves the
+GROUP_THEMES_PER_SQRT = 1.0
-# umbrella). This floor is demoted to a near-zero backstop that only rejects a literally structureless
+# Fragment-demote backstop (no-structure floor): fragment↔parent cosine is a BAD fragment
-# chain (random-pair baseline), set BELOW the legitimate heterogeneous minimum so it never kills a real model.
+# detector (measured, Markdown run: wrong demotes Blockzitate→Codeblöcke 0.353 and
-GROUP_MIN_COS_FLOOR = 0.15
-# Fragment-demote backstop, same logic as GROUP_MIN_COS_FLOOR: fragment↔parent cosine is a BAD
-# fragment detector (measured, Markdown run: wrong demotes Blockzitate→Codeblöcke 0.353 and
 # Zeichenkodierung→Überschriften 0.640 sit ABOVE any usable floor, while true NP proof-gadget
 # demotes αu-Variablen→Cook/Levin 0.172 sit low). So this only vetoes judge/panel demotes with
 # NO containment match whose pair is literally structureless (Emoji→Tabelle 0.136).
@@ -135,10 +129,15 @@ CONSENSUS_GRACE = 300
 # check loops leave any remaining objections standing after that.
 CONSENSUS_MAX_ROUNDS = 3
 
-# QA gate: after the inventory phase an automatic QA run scores the blocks; below the
+# QA gate: after the inventory phase an automatic QA run scores the blocks; below 100 %
-# threshold the flow PAUSES before board 2 burns tokens (frontend offers force-continue).
+# the flow PAUSES before board 2 burns tokens (frontend offers force-continue).
-QA_GATE_NOTE = 9.5   # 0 = gate off; quota-based, so the tolerated finding count scales with topic size
+# QA_GATE_NOTE ist nur noch der An/Aus-Schalter (> 0 = Gate aktiv) — das Gate selbst
+# öffnet ausschließlich bei 100 % (auto_loop.VOLL); Repair/Recherche arbeiten dahin.
+QA_GATE_NOTE = 9.5   # 0 = gate off
 QA_GATE_LLM = True   # include the LLM samples (Echtheit/Dubletten) in the gate run
+# Lücken-Recherche im Auto-Loop: max. gezielte Nach-Recherche-Runden pro Lauf, bevor die
+# Rest-Lücken dem Stichentscheid vorgelegt werden (Repair-Budget, keine Detektor-Konstante).
+LUECKEN_RESEARCH_MAX = 2
 
 # Inline evidence for judge agents: corpus excerpts go INTO the prompt instead of letting
 # every judge re-search the source folder (measured: ~10 tool turns/judge, 82 % of the

backend/database.py

@@ -702,6 +702,22 @@ async def set_block_status(topic: str, title_norm: str, status: str, title: str
     await _update("blocks", fields, {"topic": topic, "title_norm": title_norm})
 
 
+async def rename_block_norm(topic: str, alt_norm: str, neu_norm: str, neu_titel: str) -> None:
+    """Block-Norm vollständig um-keyen (Repair: `(n)`-Kollisionssuffix ablegen): blocks-
+    Spiegel PLUS alle angehängten Tabellen in einer Transaktion — anders als
+    set_block_status(neu_norm=…) auch mit vorhandenen Subblocks/Fragen/Artefakten sicher."""
+    async with _tx() as db:
+        for table in ("subblocks", "question_pattern", "sub_artefakte"):
+            await db.execute(
+                f"UPDATE {table} SET block_norm = ?, block = ?, updated_at = ? "
+                "WHERE topic = ? AND block_norm = ?",
+                (neu_norm, neu_titel, _now(), topic, alt_norm))
+        await db.execute(
+            "UPDATE blocks SET title_norm = ?, title = ?, updated_at = ? "
+            "WHERE topic = ? AND title_norm = ?",
+            (neu_norm, neu_titel, _now(), topic, alt_norm))
+
+
 async def delete_blocks(topic: str) -> None:
     async with _tx() as db:
         await db.execute("DELETE FROM blocks WHERE topic = ?", (topic,))
@@ -945,6 +961,35 @@ async def list_runs(topic: str, limit: int = 10) -> list[dict]:
     return out
 
 
+async def latest_board_runs(topic: str) -> dict:
+    """Jüngster Lauf MIT Daten je Ebene — Anzeige-Quelle der Board-Kopfzeilen im Frontend.
+    „Nur Artefakte"-/Guide-Läufe bekommen eine frische run_id und lassen die anderen Ebenen
+    leer; der jüngste Lauf allein zeigt dann nichts. Hier zählt je Ebene der letzte Lauf,
+    der sie wirklich enthielt. inventory/artefacts via meta.$.board (agents.agent_ebene);
+    guide via run_id-Suffix „-g"+4hex (guide_board.run_guide_board setzt den Marker,
+    Blocks-Suffixe sind reines Hex — enthalten nie „g").
+    → {ebene: {run_id, aktiv, agents, tokens, start, ende} | None}"""
+    db = await get_db()
+    out: dict = {}
+    for b in ("inventory", "artefacts"):
+        cur = await db.execute(
+            "SELECT run_id FROM events WHERE topic = ? AND kind = 'agent' AND run_id != '' "
+            "AND json_extract(meta,'$.board') = ? ORDER BY ts DESC LIMIT 1", (topic, b))
+        row = await cur.fetchone()
+        out[b] = None if row is None else {
+            "run_id": row[0], "aktiv": _current_run.get(topic) == row[0],
+            **await events_run_summary(topic, row[0], board=b)}
+    cur = await db.execute(
+        "SELECT run_id FROM events WHERE topic = ? AND kind = 'agent' AND run_id != '' "
+        "AND run_id GLOB '*-g[0-9a-f][0-9a-f][0-9a-f][0-9a-f]' ORDER BY ts DESC LIMIT 1",
+        (topic,))
+    row = await cur.fetchone()
+    out["guide"] = None if row is None else {
+        "run_id": row[0], "aktiv": _current_run.get(topic) == row[0],
+        **await events_run_summary(topic, row[0])}  # Guide: ganzer Lauf (Events sind untagged)
+    return out
+
+
 async def kanban_dead(topic: str) -> list[dict]:
     """Dead-letter cards across boards (for the board UI + requeue)."""
     return await kanban_cards(topic, stage="dead")

backend/fake_agents.py

@@ -21,7 +21,6 @@ _PATH_RE = re.compile(r"(/\S+\.(?:json|md))")
 _NUM_RE = re.compile(r"^\s*(\d+)[.)]\s+(.*\S)", re.MULTILINE)
 _SUBLIST_RE = re.compile(r"^- (?:\[(\w+)\] )?(.+\S)\s*$", re.MULTILINE)
 _ZIEL_RE = re.compile(r"\(([a-z]\d+)\)")
-_PAIR_RE = re.compile(r"^(\d+)\.\s*\nA: \[Block: (.*?)\] (.*?)\n", re.MULTILINE)
 
 
 def _norm(s: str) -> str:
@@ -30,7 +29,7 @@ def _norm(s: str) -> str:
 
 class Welt:
     """Deterministisches Themen-Modell. bloecke: {titel: {"beschreibung": str,
-    "subs": [titel]}}; optionale Regeln steuern Konsolidierung/Cross-Block."""
+    "subs": [titel]}}; optionale Regeln steuern das Störfall-Verhalten."""
 
     def __init__(self, bloecke: dict | None = None, *, gruppen: list | None = None,
                  kataloge: list | None = None, stoerungen: list | None = None):
@@ -149,8 +148,8 @@ class Welt:
         if "-supplement-beleg" in key or "-anker-beleg-" in key:
             nums = {m.group(1) for m in _NUM_RE.finditer(prompt)}
             return j({"relevant": {k: "ja" for k in sorted(nums, key=int)} or {"1": "ja"}})
-        if "-supplement" in key:
+        if "-supplement" in key or "-luecken-nachfass-" in key:
-            return j({"blocks": []})
+            return j({"blocks": []})  # Fake-Welt ist vollständig — Lücken-Research findet nichts
         if "-source-relevance-" in key:
             nums = {m.group(1) for m in _NUM_RE.finditer(prompt)}
             return j({"relevant": {k: "ja" for k in sorted(nums, key=int)} or {"1": "ja"}})
@@ -197,11 +196,6 @@ class Welt:
                       "uebernehmen": unsicher, "facts_probleme": [], "levels": {}, "relevanz": {}})
         if "-sb-fix-" in key:
             return j({"subs": []})
-        if "-sub-crossblock-" in key:
-            urteile = {}
-            for m in _PAIR_RE.finditer(prompt):
-                urteile[m.group(1)] = "a"  # identischer Text (nur so wird gepaart) → A behält
-            return j({"pairs": urteile or {"1": "nein"}})
         if "-art-gen-" in key:
             subs = self._subs_im_prompt(prompt)
             t = (self._bloecke_im_prompt(prompt) or ["?"])[0]
@@ -308,7 +302,6 @@ def aktivieren(welt: Welt, setattr_fn=setattr) -> None:
 
     import agents
     import blocks
-    import board_artefacts as ba
     import board_inventory as bi
     import guide
     import guide_board
@@ -360,7 +353,7 @@ def aktivieren(welt: Welt, setattr_fn=setattr) -> None:
         _find = staticmethod(_real_emb._find)
         _union = staticmethod(_real_emb._union)
 
-    for mod in (blocks, ba, qa, bi):
+    for mod in (blocks, qa, bi):
         setattr_fn(mod, "embedding", _FakeEmb)
     # _emb_ok bleibt echt (True über _FakeEmb): Bottom-up braucht den Grouping-Stage.
     # _FakeEmb bildet nur bei identischem Text Nachbarn — verschiedene Atome erzeugen keine

backend/guide_board.py

@@ -643,6 +643,8 @@ async def run_guide_board(guide_id: str, topic: str, format_name: str, entries:
                      is_cancelled=lambda: is_guide_cancelled(guide_id), guide_id=guide_id)
     import uuid
     from datetime import datetime, timezone
+    # „-g"+hex4-Suffix markiert Guide-Läufe (Blocks-Suffixe sind reines Hex) —
+    # database.latest_board_runs erkennt Guide-run_ids an genau diesem Muster.
     db.set_current_run(topic, f"{datetime.now(timezone.utc).strftime('%Y%m%d-%H%M')}-g{uuid.uuid4().hex[:4]}")
     try:
         spec = (TEMPLATES_DIR / "Format" / "Section.md").read_text(encoding="utf-8")
@@ -751,33 +753,58 @@ async def board_snapshot(topic: str, format_name: str, limit: int = 20) -> dict:
 
 
 async def repair_karten(topic: str, format_name: str) -> list[str]:
-    """QA-Befund-getriebenes Guide-Repair: Karten, die im jüngsten Guide-QA-Report
+    """QA-Befund-getriebenes Guide-Repair (Pendant zum Blocks-Repair: „Score unter 10
-    Befunde tragen, gehen zurück auf `pruefer` (md bleibt) — Prüfer+Fix beheben gezielt,
+    muss einen Fix-Pfad haben"). Kritische Befunde (marker_fehlend/ziel_ohne_anker/
-    generate_guide resumt die offenen Karten und misst am Ende neu. Pendant zum
+    fachlich_falsch) → zurück auf `pruefer` (brauchen Facts-/Ziele-Kontext + Re-Prüfer).
-    Blocks-Repair („Score unter 10 muss einen Fix-Pfad haben"). → betroffene Blocktitel."""
+    Reine Stil-Befunde (redundanz/laengen/lesbarkeit) → direkt auf `fix` mit expliziten
+    Auftragszeilen: der Prüfer sieht pro Karte nur die EIGENE Section und kann
+    Cross-Karten-Redundanz nie wiederfinden — der Fix bekommt den Kontext hier hinein
+    (kein KRITISCH-Präfix → genau EIN Rewrite ohne Re-Prüfer). generate_guide resumt
+    die offenen Karten und misst am Ende neu. → betroffene Blocktitel."""
     import qa as qa_mod
+    from guide_qa import block_budget, LAENGE_BAND
     reports = qa_mod.report_paths(topic, guide=True)
     rep = _json_file(reports[-1]) if reports else None
     if not rep:
         return []
     cards = {c["block_norm"]: c for c in await db.list_guide_cards(topic, format_name)}
-    norms: set[str] = set()
+    kritisch: set[str] = set()
     for e in rep.get("marker_fehlend", []):        # "Block · sub"
-        norms.add(_norm_title(str(e).split(" · ")[0]))
+        kritisch.add(_norm_title(str(e).split(" · ")[0]))
     for e in rep.get("ziel_ohne_anker", []):       # "block_norm · (id) text"
-        norms.add(str(e).split(" · ")[0])
+        kritisch.add(str(e).split(" · ")[0])
-    for e in rep.get("laengen_ausreisser", []):    # {"block": titel}
-        norms.add(_norm_title(e.get("block", "") if isinstance(e, dict) else str(e)))
-    for e in rep.get("lesbarkeit", []):            # "Block: hinweis"
-        norms.add(_norm_title(str(e).split(":")[0]))
     for t in rep.get("fachlich_falsch", []) or []:
-        norms.add(_norm_title(str(t)))
+        kritisch.add(_norm_title(str(t)))
+    stil: dict[str, list[str]] = {}
     for e in rep.get("redundanz", []):             # {"a": "Block: absatz", "b": …}
-        for seite in ("a", "b"):
+        a, b = str(e.get("a", "")), str(e.get("b", ""))
-            norms.add(_norm_title(str(e.get(seite, "")).split(":")[0]))
+        bn = _norm_title(b.split(":")[0])
+        auszug = b.split(":", 1)[1].strip() if ":" in b else b
+        stil.setdefault(bn, []).append(
+            f"- BALLAST (kürzen): Absatz doppelt zu Block «{a.split(':')[0]}» („{auszug}…\") — "
+            "hier straffen, der Inhalt bleibt im anderen Block")
+    for e in rep.get("laengen_ausreisser", []):    # {"block", "zeichen", "budget"}
+        if not isinstance(e, dict):
+            continue
+        bn = _norm_title(e.get("block", ""))
+        budget = e.get("budget") or block_budget([])
+        lo, hi = LAENGE_BAND
+        stil.setdefault(bn, []).append(
+            f"- LÄNGE: {e.get('zeichen')} Zeichen (Budget {budget}, erlaubt "
+            f"{round(lo * budget)}–{round(hi * budget)}): schreibe den ausführlich-Teil auf etwa "
+            f"{budget} Zeichen GESAMT um — Sockel-Prosa und Wiederholungen streichen, "
+            "alle Sub-Marker und Beispiele behalten")
+    for e in rep.get("lesbarkeit", []):            # "Block: hinweis"
+        bn = _norm_title(str(e).split(":")[0])
+        hint = str(e).split(":", 1)[1].strip() if ":" in str(e) else str(e)
+        stil.setdefault(bn, []).append(f"- LESBARKEIT: {hint}")
     betroffen = []
-    for n in sorted(norms & set(cards)):
+    for n in sorted((kritisch | set(stil)) & set(cards)):
-        await db.set_guide_card(topic, format_name, n, stage="pruefer", status="open", gate_info="")
+        if n in kritisch:
+            await db.set_guide_card(topic, format_name, n, stage="pruefer", status="open", gate_info="")
+        else:
+            await db.set_guide_card(topic, format_name, n, stage="fix", status="open",
+                                    gate_info="\n".join(stil[n]))
         betroffen.append(cards[n]["block"])
     return betroffen
 

backend/qa.py

@@ -11,6 +11,7 @@ previous report of the same topic.
 """
 
 import asyncio
+import hashlib
 import logging
 import re
 import sys
@@ -277,8 +278,10 @@ def hygiene(blocks: list[dict]) -> list[dict]:
 
 def _zaehlbare_luecken(lk: list[dict], llm: bool) -> list[dict]:
     """With --llm only non-refuted gaps count ('?' = unjudged stays, conservative) — refuted
-    ones dragged the note although the judge cleared them (aak: 5 of 8, weight 3.0)."""
+    ones dragged the note although the judge cleared them (aak: 5 of 8, weight 3.0).
-    return [x for x in lk if x.get("llm") != "nein"] if llm else lk
+    Persistierte Freisprüche (2:1 im Repair) zählen nie."""
+    offen = [x for x in lk if not x.get("freispruch")]
+    return [x for x in offen if x.get("llm") != "nein"] if llm else offen
 
 
 def note(quoten: dict, gewichte: dict = NOTE_GEWICHTE) -> float:
@@ -335,11 +338,13 @@ def _qa_prompt(name: str, **kwargs) -> str:
 
 
 async def judge_wave(template: str, topic: str, key: str, slot: str, items: list[str],
-                     *, chunk: int = JUDGE_CHUNK, prefix: str = "qa", label: str = "QA") -> dict[int, str]:
+                     *, chunk: int = JUDGE_CHUNK, prefix: str = "qa", label: str = "QA",
+                     extra: str = "") -> dict[int, str]:
     """Gechunkte Ja/Nein-Judge-Welle über ALLE Items, Chunks parallel (die Semaphoren in
     agents.py begrenzen); Ergebnis mit globalen 1-basierten Indizes. Fail-open pro Chunk
     (Items bleiben ohne Urteil), aber nie stumm. Ersetzt die drei strukturgleichen
-    Handkopien in repair/qa/guide_qa."""
+    Handkopien in repair/qa/guide_qa. `extra` füllt den {extra}-Slot des Templates
+    (z. B. Inventar-Kontext für das Lücken-Urteil im Repair)."""
     from agents import run_agent
     from pipeline import _timeout, _yesno_schema
     from jsonio import parse_json_text
@@ -349,7 +354,7 @@ async def judge_wave(template: str, topic: str, key: str, slot: str, items: list
         listing = "\n\n".join(f"{k}. {it}" for k, it in enumerate(teil, 1))
         try:
             rc, out, _err = await run_agent(
-                f"{prefix}-{topic}-{key}-{lo}", _qa_prompt(template, topic=topic, extra="", **{slot: listing}),
+                f"{prefix}-{topic}-{key}-{lo}", _qa_prompt(template, topic=topic, extra=extra, **{slot: listing}),
                 _timeout("qa_judge"), role="judge", capabilities="none", scope=topic, label=f"{label} {key}")
         except Exception:
             log.exception("[%s] %s-Judge %s+%d fehlgeschlagen — Items ohne Urteil", topic, label, key, lo)
@@ -406,6 +411,22 @@ def _paar_key(a: str, b: str) -> str:
     return "||".join(sorted((_norm_title(a), _norm_title(b))))
 
 
+def luecken_key(item: dict) -> str:
+    """Stabiler Freispruch-Schlüssel einer Lücken-Fundstelle: Datei + Vorschau-Hash.
+    Abschnittsnummern verschieben sich bei Korpusänderung — dann veralten die Keys
+    und werden inert (gewollt: neue Fundstellen brauchen ein neues Urteil)."""
+    v = " ".join(str(item.get("vorschau", "")).casefold().split())
+    return f"{item.get('datei', '')}||{hashlib.sha1(v.encode()).hexdigest()[:16]}"
+
+
+def offene_luecken(report: dict) -> tuple[list[dict], list[str]]:
+    """Zählbare offene Lücken eines Reports: (luecken-Items ohne Freispruch/LLM-nein,
+    konzept_luecken-Namen). Grundlage für Lücken-Research und Lücken-Urteil im Repair."""
+    lk = [x for x in report.get("luecken", [])
+          if not x.get("freispruch") and x.get("llm") != "nein"]
+    return lk, list(report.get("konzept_luecken", []))
+
+
 def lade_freispruch(topic: str) -> dict[str, list[str]]:
     """Persistierte 2:1-Freisprüche des Repair-Stichentscheids (repair._mit_stichentscheid):
     mehrheitlich als „behalten" geurteilte Befunde zählen nicht mehr in die Note — sonst
@@ -445,16 +466,31 @@ async def qa_report(topic: str, llm: bool = False) -> dict | None:
     frei_fremd = set(frei.get("fremd") or [])
     fremd_frei = [t for t in fr if _norm_title(t) in frei_fremd]
     fr = [t for t in fr if _norm_title(t) not in frei_fremd]
+    # Persistierte 2:1-Freisprüche: markiert bleibt sichtbar (diffbar), zählt aber nicht mehr
+    # in Quote und Judge-Welle — sonst pendelte der Verdachts-Floor ewig unter 10.
+    frei_dub = set(frei.get("dubletten") or [])
+    for p in d:
+        if _paar_key(p["a"], p["b"]) in frei_dub:
+            p["freispruch"] = True
+    d_offen = [p for p in d if not p.get("freispruch")]
+    frei_lk = set(frei.get("luecken") or [])
+    for x in lk:
+        if luecken_key(x) in frei_lk:
+            x["freispruch"] = True
+    lk_offen = [x for x in lk if not x.get("freispruch")]
+    frei_kl = set(frei.get("konzept_luecken") or [])
+    kl_frei = [nm for nm in kl if _norm_title(nm) in frei_kl]
+    kl = [nm for nm in kl if _norm_title(nm) not in frei_kl]
 
-    if llm and d:
+    if llm and d_offen:
         v = await judge_wave("QA-Dubletten", topic, "dubletten", "pairs",
-                             [f"A: {p['a']}\nB: {p['b']}" for p in d[:LLM_SAMPLE]])
+                             [f"A: {p['a']}\nB: {p['b']}" for p in d_offen[:LLM_SAMPLE]])
-        for k, p in enumerate(d[:LLM_SAMPLE], 1):
+        for k, p in enumerate(d_offen[:LLM_SAMPLE], 1):
             p["llm"] = v.get(k, "?")
-    if llm and lk:
+    if llm and lk_offen:
         v = await judge_wave("QA-Luecken", topic, "luecken", "sections",
-                             [f"[{x['datei']} #{x['abschnitt']}] {x['vorschau']}" for x in lk[:LLM_SAMPLE]])
+                             [f"[{x['datei']} #{x['abschnitt']}] {x['vorschau']}" for x in lk_offen[:LLM_SAMPLE]])
-        for k, x in enumerate(lk[:LLM_SAMPLE], 1):
+        for k, x in enumerate(lk_offen[:LLM_SAMPLE], 1):
             x["llm"] = v.get(k, "?")
     if llm and sd:  # full coverage in chunks — a sampled quota would mislead the note
         v = await judge_wave("QA-Sub-Dubletten", topic, "sub-dubletten", "pairs",
@@ -502,7 +538,7 @@ async def qa_report(topic: str, llm: bool = False) -> dict | None:
         "topic": topic, "erstellt": datetime.now(timezone.utc).isoformat(),
         "run_id": summary.get("run_id", ""), "bloecke": len(blocks),
         "quoten": {
-            "dubletten_verdacht": round(len(d) / max(len(blocks), 1), 3),
+            "dubletten_verdacht": round(len(d_offen) / max(len(blocks), 1), 3),
             "luecken": round(len(_zaehlbare_luecken(lk, llm)) / n_sections, 3),
             "fremd": round(len(fr) / max(len(blocks), 1), 3),
             **({"konzept_luecken": round(len(kl) / max(len(named), 1), 3)} if corpus else {}),
@@ -512,6 +548,7 @@ async def qa_report(topic: str, llm: bool = False) -> dict | None:
         "quoten_artefakte": quoten_art,
         **({"unecht": unecht} if unecht is not None else {}),
         **({"fremd_freigesprochen": fremd_frei} if fremd_frei else {}),
+        **({"konzept_luecken_freigesprochen": kl_frei} if kl_frei else {}),
         "dubletten": d, "sub_dubletten": sd, "luecken": lk, "konzept_luecken": kl,
         "fremd": fr, "beleg": bl, "hygiene": hy,
         "artefakte": art,

backend/repair.py

@@ -2,16 +2,17 @@
 
 Blindes Re-Filtern reproduziert die blinden Flecken der Pipeline (sie hat die Befunde ja
 durchgelassen). Hier fließen die QA-BEFUNDE als Input in gezielte Aktionen: Hygiene
-deterministisch, bestätigte Dubletten mergen (Zweitmeinung), Fremd/Unecht nur nach
+deterministisch (+ Beschreibung/Suffix per Sanierung/Rename), bestätigte Dubletten mergen
-Gegen-Judge entfernen (fail-open: Zweifel/Fehler → behalten). Lücken brauchen Recherche,
+(Zweitmeinung), Fremd/Unecht nur nach Gegen-Judge entfernen, Beleg-Nachfass je Sub,
-Verwaiste den nächsten Board-2-Lauf — beides wird nur ausgewiesen."""
+Lücken per Stichentscheid klären (Freispruch oder bestätigt = braucht Recherche).
+Fail-open überall: Zweifel/Judge-Fehler → behalten, nichts persistieren."""
 
 import logging
 import re
 
 import database as db
 import qa
-from blocks import _blocks_files, _evidence_pack, source_folder
+from blocks import _blocks_files, _evidence_pack, material_folder, source_folder
 from config import EVIDENCE_PER_BLOCK
 from fsutil import atomic_write_json
 from jsonio import read_json_file as _json_file
@@ -20,9 +21,12 @@ from textkit import _norm_title, _title, clean_title, parse_facts
 log = logging.getLogger("creator.repair")
 
 
-async def repair_befunde(topic: str, ebene: str | None = None) -> dict:
+async def repair_befunde(topic: str, ebene: str | None = None, luecken_urteil: bool = True) -> dict:
-    """ebene=None → alle Fixes; „inventory" → nur Inventar (Hygiene/Merges/Fremd);
+    """ebene=None → alle Fixes; „inventory" → nur Inventar; „artefacts" → nur Artefakte.
-    „artefacts" → nur Artefakte (Sub-Merges/Waisen). Misst am Ende IMMER beide Noten neu."""
+    luecken_urteil: offene Lücken/Konzept-Lücken dem Stichentscheid vorlegen (Freispruch
+    oder bestätigt) — der QA-Gate-Watch schaltet es aus, solange seine Lücken-Recherche
+    noch Runden hat. Misst am Ende IMMER beide Noten neu. `aktionen` zählt alles, was die
+    Runde getan hat (Fixes+Merges+Freisprüche) — der Auto-Loop stoppt erst bei 0."""
     reports = qa.report_paths(topic)
     report = _json_file(reports[-1]) if reports else None
     if not report:
@@ -34,9 +38,13 @@ async def repair_befunde(topic: str, ebene: str | None = None) -> dict:
     art = ebene in (None, "artefacts")
 
     hygiene = await _fix_hygiene(topic, report, by_norm, files) if inv else []
-    merges = await _merge_dubletten(topic, report, by_norm, files) if inv else []
+    hygiene += (await _fix_beschreibungen(topic, report, by_norm)) if inv else []
+    hygiene += (await _fix_suffixe(topic, report, by_norm, files)) if inv else []
+    merges, frei_paare = (await _merge_dubletten(topic, report, by_norm, files)) if inv else ([], [])
     sub_merges, frei_subs = (await _merge_sub_dubletten(topic, report, files)) if art else ([], [])
     entfernt, frei_bloecke = (await _entferne_fremd_unecht(topic, report, by_norm, files)) if inv else ([], [])
+    frei_luecken = (await _pruefe_luecken(topic, report, by_norm)) if inv and luecken_urteil else []
+    beleg_fix = (await _belege_nachfassen(topic, report, files)) if art else []
     aufgeraeumt = (await _raeume_waisen(topic)) if art else 0
 
     # llm=True: gleiche Messlatte wie QA-Button/Abschluss-QA — der llm=False-Report
@@ -45,16 +53,22 @@ async def repair_befunde(topic: str, ebene: str | None = None) -> dict:
     if neu:
         await qa.write_report(neu)
     na = neu.get("note_artefakte") if neu else None
+    freigesprochen = frei_paare + frei_subs + frei_bloecke + frei_luecken
+    lk_rest, kl_rest = qa.offene_luecken(neu or {})
     return {"hygiene": hygiene, "merges": merges, "sub_merges": sub_merges, "entfernt": entfernt,
-            "aufgeraeumt": aufgeraeumt, "freigesprochen": frei_subs + frei_bloecke,
+            "beleg_fix": beleg_fix, "aufgeraeumt": aufgeraeumt, "freigesprochen": freigesprochen,
-            "braucht_research": len(report.get("luecken", [])),
+            "aktionen": (len(hygiene) + len(merges) + len(sub_merges) + len(entfernt)
+                         + len(beleg_fix) + aufgeraeumt + len(freigesprochen)),
+            "braucht_research": len(lk_rest) + len(kl_rest),  # offene Lücken NACH dieser Runde
             "note": float(neu["note"]) if neu else 10.0,          # neu gemessene Inventar-Note
             "note_artefakte": float(na) if na is not None else None}  # None solange Board 2 leer
 
 
-async def _judge(template: str, topic: str, key: str, slot: str, items: list[str]) -> dict[int, str]:
+async def _judge(template: str, topic: str, key: str, slot: str, items: list[str],
+                 extra: str = "") -> dict[int, str]:
     """No-Tool-Judge-Welle (fail-open: Fehler → leeres Verdikt = behalten)."""
-    return await qa.judge_wave(template, topic, key, slot, items, prefix="repair", label="Repair")
+    return await qa.judge_wave(template, topic, key, slot, items, prefix="repair", label="Repair",
+                               extra=extra)
 
 
 def _speichere_freispruch(topic: str, kategorie: str, keys: list[str]) -> None:
@@ -67,7 +81,7 @@ def _speichere_freispruch(topic: str, kategorie: str, keys: list[str]) -> None:
 
 async def _mit_stichentscheid(template: str, topic: str, key: str, slot: str,
                               lines: list[str], befund: str, kategorie: str = "",
-                              ids: list[str] | None = None) -> tuple[dict[int, str], list[str]]:
+                              ids: list[str] | None = None, extra: str = "") -> tuple[dict[int, str], list[str]]:
     """Zweitmeinung + Stichentscheid: Der Repair-Judge kann den QA-Befund kippen — bei
     Dissens (QA sagt Befund, Judge sagt behalten) entscheidet ein DRITTER Judge nur über
     die strittigen Items, Mehrheit 2/3 (Muster Crossblock-Tiebreaker). Ohne ihn pendelte
@@ -76,11 +90,11 @@ async def _mit_stichentscheid(template: str, topic: str, key: str, slot: str,
     Explizites 2:1-„behalten" wird als FREISPRUCH persistiert (kategorie+ids) — die QA
     zählt das Item ab dann nicht mehr (qa.lade_freispruch). j3-AUSFALL persistiert nicht
     (fail-open ist kein Urteil). → (verdicts, freigesprochene Zeilen)."""
-    v = await _judge(template, topic, key, slot, lines)
+    v = await _judge(template, topic, key, slot, lines, extra=extra)
     strittig = [i for i in range(1, len(lines) + 1) if v.get(i) != befund]
     frei: list[str] = []
     if strittig:
-        v3 = await _judge(template, topic, f"{key}-st", slot, [lines[i - 1] for i in strittig])
+        v3 = await _judge(template, topic, f"{key}-st", slot, [lines[i - 1] for i in strittig], extra=extra)
         gegen = "nein" if befund == "ja" else "ja"
         frei_keys: list[str] = []
         for pos, i in enumerate(strittig, 1):
@@ -95,9 +109,165 @@ async def _mit_stichentscheid(template: str, topic: str, key: str, slot: str,
     return v, frei
 
 
+async def _fix_beschreibungen(topic: str, report: dict, by_norm: dict) -> list[str]:
+    """Hygiene-Resttyp „leere-beschreibung": EINE Beschreibung aus Material-Auszügen
+    generieren (Blocks-Sanierung-Template; der Titel bleibt — Repair ist flow-los und
+    hat keinen Korpus-Anker-Kontext für Renames). Ohne Material/Auszüge bleibt der Befund."""
+    from agents import run_agent
+    from pipeline import _prompt, _timeout
+    from jsonio import parse_json_text
+    from board_inventory import _sanierung_schema
+    items = [h for h in report.get("hygiene", []) if "leere-beschreibung" in (h.get("probleme") or [])]
+    folder = source_folder(topic) or material_folder(topic)
+    if not items or not folder:
+        return []
+    out: list[str] = []
+    for h in items:
+        norm = _norm_title(h.get("titel", ""))
+        card = by_norm.get(norm)
+        if not card or (card["payload"].get("description") or "").strip():
+            continue
+        titel = card["payload"].get("title", "")
+        ev = _evidence_pack(folder, card["payload"].get("sources") or None, [titel], budget=4000)
+        if not ev:
+            continue
+        try:
+            rc, txt, _err = await run_agent(
+                f"repair-{topic}-sanierung-{norm[:24]}",
+                _prompt("Blocks-Sanierung", topic=topic, title=titel, description="(leer)", excerpts=ev),
+                _timeout("qa_judge"), role="judge", capabilities="none", scope=topic,
+                label="Repair Beschreibung")
+        except Exception:
+            log.exception("[%s] Beschreibungs-Sanierung fehlgeschlagen — Befund bleibt", topic)
+            continue
+        verdict = _sanierung_schema(parse_json_text(txt)) if rc == 0 else None
+        if not verdict or not verdict[1].strip():
+            continue
+        p = dict(card["payload"])
+        p["description"] = verdict[1].strip()
+        await db.kanban_set_payload(topic, "inventory", card["card_id"], p)
+        await db.set_block_status(topic, norm, "consensus", description=p["description"])
+        card["payload"] = p
+        out.append(f"beschrieben: {titel}")
+    return out
+
+
+_SUFFIX_RE = re.compile(r"\s*\(\d+\)\s*$")
+
+
+async def _fix_suffixe(topic: str, report: dict, by_norm: dict, files: dict) -> list[str]:
+    """Hygiene-Resttyp „kollisions-suffix" („Titel (2)", entstanden beim Spiegeln):
+    Basis-Norm frei (Partner inzwischen gemerged/verworfen) → Rename auf den Basistitel
+    inkl. Re-Key aller angehängten Tabellen (db.rename_block_norm) + Board-2-Karte +
+    Sidecars. Basis besetzt → Judge entscheidet Dublette (Merge); sonst bleibt der
+    Befund sichtbar (zwei echte gleichnamige Konzepte sind ein Naming-Problem)."""
+    items = [h for h in report.get("hygiene", []) if "kollisions-suffix" in (h.get("probleme") or [])]
+    out: list[str] = []
+    for h in items:
+        alt = h.get("titel", "")
+        basis = _SUFFIX_RE.sub("", alt).strip()
+        alt_norm, basis_norm = _norm_title(alt), _norm_title(basis)
+        card = by_norm.get(alt_norm)
+        if not card or not basis or basis_norm == alt_norm:
+            continue
+        if basis_norm in by_norm:  # Basis lebt noch → Dubletten-Frage statt Rename
+            merged, _frei = await _merge_dubletten(
+                topic, {"dubletten": [{"a": basis, "b": alt, "llm": "?"}]}, by_norm, files)
+            out += [f"suffix-merge: {z}" for z in merged]
+            continue
+        await db.rename_block_norm(topic, alt_norm, basis_norm, basis)
+        b2 = await db.kanban_get_card(topic, "artefacts", alt_norm)
+        if b2:
+            p2 = dict(b2["payload"])
+            p2["title"] = basis
+            await db.kanban_upsert_card(topic, "artefacts", basis_norm, b2["kind"], b2["stage"], p2)
+            await db.kanban_delete_card(topic, "artefacts", alt_norm)
+        p = dict(card["payload"])
+        p["title"] = basis
+        if p.get("mirrored_norm"):
+            p["mirrored_norm"] = basis_norm
+        await db.kanban_set_payload(topic, "inventory", card["card_id"], p)
+        card["payload"] = p
+        _rename_in_files(files, alt_norm, basis)
+        by_norm.pop(alt_norm, None)
+        by_norm[basis_norm] = card
+        out.append(f"suffix: {alt} → {basis}")
+    return out
+
+
+async def _pruefe_luecken(topic: str, report: dict, by_norm: dict) -> list[str]:
+    """Lücken-Urteil (2:1): offene luecken-Fundstellen und konzept_luecken-Namen dem
+    Stichentscheid vorlegen — 2:1-„keine echte Lücke" wird als Freispruch persistiert,
+    bestätigte bleiben als braucht_research sichtbar (Gate-Watch recherchiert, der Nutzer
+    klickt „+ Recherche"). Das Inventar geht als Kontext in den {extra}-Slot, damit die
+    Judges Abdeckung gegen den Bestand prüfen können."""
+    lk, kl = qa.offene_luecken(report)
+    if not lk and not kl:
+        return []
+    extra = ("\n\nEXISTING INVENTORY BLOCKS (judge coverage against these):\n"
+             + "\n".join(f"- {c['payload'].get('title', '')}" for c in by_norm.values()))
+    frei: list[str] = []
+    if lk:
+        _v, f = await _mit_stichentscheid(
+            "QA-Luecken", topic, "luecken", "sections",
+            [f"[{x.get('datei')} #{x.get('abschnitt')}] {x.get('vorschau', '')}" for x in lk],
+            "ja", kategorie="luecken", ids=[qa.luecken_key(x) for x in lk], extra=extra)
+        frei += f
+    if kl:
+        _v, f = await _mit_stichentscheid(
+            "QA-Konzept-Luecken", topic, "konzept-luecken", "results", list(kl),
+            "ja", kategorie="konzept_luecken", ids=[_norm_title(n) for n in kl], extra=extra)
+        frei += f
+    return frei
+
+
+async def _belege_nachfassen(topic: str, report: dict, files: dict) -> list[str]:
+    """subs_ohne_beleg (mentions=0): Beleg-Nachfass je Sub mit Material-Auszügen.
+    Judge+QA einig „nein" (kein Beleg) → Sub verwerfen (Artefakte/Fragen räumt das
+    nachlaufende _raeume_waisen); 2:1-„ja" → mentions=1 nachtragen — Datenfix am
+    gemessenen Datum selbst, kein Freispruch nötig, Detektor unverändert. Produktiv ist
+    der Detektor derzeit inaktiv (alle Schreiber setzen mentions=1) — Pfad ist Robustheit.
+    Ohne Quellordner kein Urteil möglich → Befund bleibt."""
+    eintraege = (report.get("beleg") or {}).get("subs_ohne_beleg") or []
+    folder = source_folder(topic) or material_folder(topic)
+    if not eintraege or not folder:
+        return []
+    rows = {f"{r['block']} · {r['sub_title']}": r for r in await db.list_subblocks(topic)
+            if r["status"] != "variant"}
+    items = [(e, rows[e]) for e in eintraege if e in rows and not rows[e]["mentions"]]
+    if not items:
+        return []
+    lines = []
+    for e, r in items:
+        ev = _evidence_pack(folder, None, [r["block"], r["sub_title"]], budget=EVIDENCE_PER_BLOCK)
+        lines.append(f"{e}\n{ev or '(keine Treffer im Material)'}")
+    v1 = await _judge("QA-Repair-Beleg", topic, "beleg", "blocks", lines)
+    strittig = [i for i in range(1, len(items) + 1) if v1.get(i) == "ja"]
+    v3 = (await _judge("QA-Repair-Beleg", topic, "beleg-st", "blocks",
+                       [lines[i - 1] for i in strittig])) if strittig else {}
+    out: list[str] = []
+
+    async def _verwerfen(e: str, r: dict):
+        await db.set_subblock_fields(topic, r["block_norm"], r["sub_norm"], status="discarded")
+        _entferne_sub_in_files(files, r["block_norm"], r["sub_norm"])
+        out.append(f"entfernt: {e[:60]}")
+
+    for i, (e, r) in enumerate(items, 1):
+        if v1.get(i) == "nein":  # QA (mentions=0) + Judge einig → weg
+            await _verwerfen(e, r)
+        elif v1.get(i) == "ja":  # Dissens → Stichentscheid
+            pos = strittig.index(i) + 1
+            if v3.get(pos) == "ja":
+                await db.set_subblock_fields(topic, r["block_norm"], r["sub_norm"], mentions=1)
+                out.append(f"belegt: {e[:60]}")
+            elif v3.get(pos) == "nein":
+                await _verwerfen(e, r)
+    return out
+
+
 async def _fix_hygiene(topic: str, report: dict, by_norm: dict, files: dict) -> list[str]:
     """Nur der norm-invariante Teil (`**`/Backticks); `(n)`-Suffix und leere Beschreibung
-    ändern die Norm bzw. brauchen Inhalt — bleiben Befund."""
+    ändern die Norm bzw. brauchen Inhalt — eigene Handler (_fix_suffixe/_fix_beschreibungen)."""
     fixed = []
     for h in report.get("hygiene", []):
         alt = h.get("titel", "")
@@ -117,33 +287,68 @@ async def _fix_hygiene(topic: str, report: dict, by_norm: dict, files: dict) ->
     return fixed
 
 
-async def _merge_dubletten(topic: str, report: dict, by_norm: dict, files: dict) -> list[str]:
+async def _merge_paar(topic: str, p: dict, by_norm: dict, files: dict) -> str | None:
-    """Nur QA-bestätigte Paare (llm=ja); eine Zweitmeinung, Merge nur bei erneut ja.
+    """Ein bestätigtes Dubletten-Paar mergen (spiegelt die dedup-Stage: Union ins
-    Merge spiegelt die dedup-Stage: Union ins Gewinner-Payload, Verlierer → grouped."""
+    Gewinner-Payload, Verlierer → grouped). → Journalzeile oder None."""
-    paare = [p for p in report.get("dubletten", []) if p.get("llm") == "ja"
+    a, b = by_norm.get(_norm_title(p["a"])), by_norm.get(_norm_title(p["b"]))
-             and _norm_title(p.get("a", "")) in by_norm and _norm_title(p.get("b", "")) in by_norm]
+    if not a or not b or a["card_id"] == b["card_id"]:
-    if not paare:
+        return None
-        return []
+    win, lose = sorted((a, b), key=lambda c: (len(c["payload"].get("description") or ""),
-    v, _frei = await _mit_stichentscheid("QA-Dubletten", topic, "dubletten", "pairs",
+                                              len(c["payload"].get("title") or "")), reverse=True)
-                                         [f"A: {p['a']}\nB: {p['b']}" for p in paare], "ja")
+    wp, lp = dict(win["payload"]), dict(lose["payload"])
-    merged = []
+    wp["readers"] = sorted(set(wp.get("readers") or []) | set(lp.get("readers") or []))
-    for i, p in enumerate(paare, 1):
+    wp["sources"] = sorted(set(wp.get("sources") or []) | set(lp.get("sources") or []))
-        a, b = by_norm.get(_norm_title(p["a"])), by_norm.get(_norm_title(p["b"]))
+    lp.update(reason="merged", merged_into=wp.get("title", ""))
-        if v.get(i) != "ja" or not a or not b or a["card_id"] == b["card_id"]:
+    await db.kanban_set_payload(topic, "inventory", win["card_id"], wp)
-            continue
+    await db.kanban_set_payload(topic, "inventory", lose["card_id"], lp)
-        win, lose = sorted((a, b), key=lambda c: (len(c["payload"].get("description") or ""),
+    await db.kanban_advance(topic, "inventory", lose["card_id"], "grouped")
-                                                  len(c["payload"].get("title") or "")), reverse=True)
+    await _purge_block(topic, lp.get("title", ""), files)
-        wp, lp = dict(win["payload"]), dict(lose["payload"])
+    by_norm.pop(_norm_title(lp.get("title", "")), None)
-        wp["readers"] = sorted(set(wp.get("readers") or []) | set(lp.get("readers") or []))
+    return f"{lp.get('title')} → {wp.get('title')}"
-        wp["sources"] = sorted(set(wp.get("sources") or []) | set(lp.get("sources") or []))
+
-        lp.update(reason="merged", merged_into=wp.get("title", ""))
+
-        await db.kanban_set_payload(topic, "inventory", win["card_id"], wp)
+async def _merge_dubletten(topic: str, report: dict, by_norm: dict, files: dict) -> tuple[list[str], list[str]]:
-        await db.kanban_set_payload(topic, "inventory", lose["card_id"], lp)
+    """QA-bestätigte Paare (llm=ja): Zweitmeinung, Merge nur bei erneut ja; 2:1-„behalten"
-        await db.kanban_advance(topic, "inventory", lose["card_id"], "grouped")
+    persistiert jetzt als Freispruch (fehlte — die Paare pendelten ewig im Verdacht).
-        await _purge_block(topic, lp.get("title", ""), files)
+    Widerlegte/unbeurteilte Paare (llm=nein/?) bekommen den Klärungskanal: Judge-„nein" →
-        by_norm.pop(_norm_title(lp.get("title", "")), None)
+    Freispruch (mit QA-nein 2:0; beim bloßen Verdacht reicht das klare Gegen-Urteil),
-        merged.append(f"{lp.get('title')} → {wp.get('title')}")
+    Judge-„ja" → Stichentscheid (ja → Merge 2:1, nein → Freispruch 2:1, Ausfall → nichts)."""
-    return merged
+    alle = [p for p in report.get("dubletten", []) if not p.get("freispruch")
+            and _norm_title(p.get("a", "")) in by_norm and _norm_title(p.get("b", "")) in by_norm]
+    ja = [p for p in alle if p.get("llm") == "ja"]
+    offen = [p for p in alle if p.get("llm") != "ja"]
+    merged: list[str] = []
+    frei: list[str] = []
+    if ja:
+        v, f = await _mit_stichentscheid("QA-Dubletten", topic, "dubletten", "pairs",
+                                         [f"A: {p['a']}\nB: {p['b']}" for p in ja], "ja",
+                                         kategorie="dubletten",
+                                         ids=[qa._paar_key(p["a"], p["b"]) for p in ja])
+        frei += f
+        for i, p in enumerate(ja, 1):
+            if v.get(i) == "ja" and (zeile := await _merge_paar(topic, p, by_norm, files)):
+                merged.append(zeile)
+    if offen:
+        ids = [qa._paar_key(p["a"], p["b"]) for p in offen]
+        v1 = await _judge("QA-Dubletten", topic, "dubletten-v", "pairs",
+                          [f"A: {p['a']}\nB: {p['b']}" for p in offen])
+        frei_keys = [ids[i - 1] for i in range(1, len(offen) + 1) if v1.get(i) == "nein"]
+        frei += [f"{offen[i - 1]['a']} <-> {offen[i - 1]['b']}"[:80]
+                 for i in range(1, len(offen) + 1) if v1.get(i) == "nein"]
+        strittig = [i for i in range(1, len(offen) + 1) if v1.get(i) == "ja"]
+        if strittig:
+            v3 = await _judge("QA-Dubletten", topic, "dubletten-v-st", "pairs",
+                              [f"A: {offen[i - 1]['a']}\nB: {offen[i - 1]['b']}" for i in strittig])
+            for pos, i in enumerate(strittig, 1):
+                if v3.get(pos) == "ja" and (zeile := await _merge_paar(topic, offen[i - 1], by_norm, files)):
+                    merged.append(zeile)
+                elif v3.get(pos) == "nein":
+                    frei_keys.append(ids[i - 1])
+                    frei.append(f"{offen[i - 1]['a']} <-> {offen[i - 1]['b']}"[:80])
+        if frei_keys:
+            _speichere_freispruch(topic, "dubletten", frei_keys)
+            log.info("[%s] Repair dubletten: %d Verdacht(e) freigesprochen", topic, len(frei_keys))
+    return merged, frei
 
 
 _SUB_PAAR = re.compile(r"^\[(.+?)\] (.+)$", re.S)

backend/routes.py

@@ -20,7 +20,7 @@ from database import (
     delete_topic_pipeline, delete_source, get_guide_content, delete_guide_content,
     get_sub_artefakte, kanban_reset, delete_guide_board,
     get_practice_progress, upsert_practice_progress, sub_levels_norm, subs_per_level_norm,
-    list_runs, get_db,
+    list_runs, latest_board_runs, get_db,
 )
 from textkit import _norm_title
 from blocks import generate_blocks, cancel_blocks, blocks_status, active_blocks, reset_blocks, load_source, load_overview, subblocks_title, subblocks_frei, load_question_pattern, load_question_pattern_free, _blocks_files
@@ -82,8 +82,10 @@ async def health():
 
 @router.get("/runs")
 async def get_runs(topic: str, limit: int = 10):
-    """Lauf-Historie (Blocks + Guide): Zeitspanne, Agenten, Tokens, Fehler je run_id."""
+    """Lauf-Historie (Blocks + Guide): Zeitspanne, Agenten, Tokens, Fehler je run_id.
-    return {"runs": await list_runs(topic, limit)}
+    `latest` = jüngster Lauf MIT Daten je Ebene (inventory/artefacts/guide) — die
+    Board-Kopfzeilen zeigen so auch nach „Nur Artefakte"-/Guide-Läufen ihre Zahlen."""
+    return {"runs": await list_runs(topic, limit), "latest": await latest_board_runs(topic)}
 
 
 @router.get("/topics/progress")

backend/tests/test_agents_api.py

@@ -273,12 +273,12 @@ def test_meminfo_reads_proc():
 
 
 def test_agent_ebene_klassifiziert_board():
-    """Board-2-Marker (art-/sb-/crossblock/outline) → artefacts; alles andere → inventory."""
+    """Board-2-Marker (art-/sb-/outline) → artefacts; alles andere → inventory."""
     T = "shopware"
     for key in (f"blocks-{T}-research-a1", f"blocks-{T}-pair-x", f"blocks-{T}-naming-y",
                 f"blocks-{T}-gruppierung-h-cTOP", f"blocks-{T}-dedup-z"):
         assert agents.agent_ebene(key) == "inventory", key
     for key in (f"blocks-{T}-alpha-sb-enrich-h", f"blocks-{T}-alpha-sb-verify-h-j1",
                 f"blocks-{T}-alpha-art-gen-h-t1", f"blocks-{T}-alpha-art-check-h",
-                f"blocks-{T}-sub-crossblock-h-j1", f"blocks-{T}-outline-judge"):
+                f"blocks-{T}-outline-judge"):
         assert agents.agent_ebene(key) == "artefacts", key

backend/tests/test_auto_loop.py

@@ -1,4 +1,4 @@
-"""Auto-Repair-Loop-Primitive: Stopp bei 100 %, Stillstand, Limit."""
+"""Auto-Repair-Loop-Primitive: Stopp bei 100 %, Stillstand (unbewegt), Limit."""
 import auto_loop
 
 
@@ -14,7 +14,7 @@ async def test_verbessert_bis_voll():
     noten = iter([9.0, 10.0])
 
     async def rep():
-        return next(noten)
+        return next(noten), True
 
     r = await auto_loop.auto_repair_loop("inv", 8.0, rep)  # 8.0 → 9.0 → 10.0
     assert r["grund"] == "fertig" and r["runden"] == 2
@@ -22,19 +22,31 @@ async def test_verbessert_bis_voll():
 
 async def test_stillstand():
     async def rep():
-        return 8.0  # Repair bewegt nichts
+        return 8.0, False  # nichts getan, Note steht
 
     r = await auto_loop.auto_repair_loop("art", 8.0, rep)
     assert r["grund"] == "stillstand" and r["runden"] == 1
     assert r["note"] == 8.0
 
 
+async def test_bewegt_ohne_notengewinn_laeuft_weiter():
+    """Eine bewegte Runde (z. B. Lücken-Research senkt die Note transient) ist KEIN
+    Stillstand — erst unbewegt + keine Verbesserung stoppt; max_iter begrenzt Livelocks."""
+    laeufe = iter([(7.5, True), (8.0, True), (8.0, False)])
+
+    async def rep():
+        return next(laeufe)
+
+    r = await auto_loop.auto_repair_loop("inv", 8.0, rep)
+    assert r["grund"] == "stillstand" and r["runden"] == 3
+
+
 async def test_limit():
     stand = {"n": 1.0}
 
     async def rep():
         stand["n"] += 0.1  # verbessert stetig, erreicht aber nie 10.0
-        return stand["n"]
+        return stand["n"], True
 
     r = await auto_loop.auto_repair_loop("guide", 1.0, rep, max_iter=10)
     assert r["grund"] == "limit" and r["runden"] == 10

backend/tests/test_board_inventory.py

@@ -103,12 +103,6 @@ async def board_env(testdb, tmp_path, monkeypatch):
                      ("_artefakte_block", fake_artefakte), ("_outline_block", fake_outline)]:
         monkeypatch.setattr(ba, name, fn)
 
-    class _EmbOff:  # Cross-Block-Barrier reicht ohne Modell alle Karten durch
-        @staticmethod
-        def available():
-            return False
-    monkeypatch.setattr(ba, "embedding", _EmbOff)
-
     work = tmp_path / "arbeit"
     work.mkdir()
     files = {"arbeit": work, "final": tmp_path / "blocks.md",
@@ -973,8 +967,8 @@ async def test_qa_gate_auto_stillstand_pauses(board_env, monkeypatch):
     async def bad_qa(topic, llm=False):
         return {"note": 5.0, "topic": TOPIC, "quoten": {}, "fremd": [], "artefakte": {}}
 
-    async def stuck_repair(topic, ebene=None):
+    async def stuck_repair(topic, ebene=None, luecken_urteil=True):
-        return {"note": 5.0}  # bewegt nichts
+        return {"note": 5.0, "aktionen": 0}  # bewegt nichts
 
     monkeypatch.setattr(qa_mod, "qa_report", bad_qa)
     monkeypatch.setattr(qa_mod, "_write_report", lambda r: None)
@@ -988,6 +982,45 @@ async def test_qa_gate_auto_stillstand_pauses(board_env, monkeypatch):
     assert await db.kanban_count(TOPIC, "done_artefact", board="artefacts") == 0
 
 
+async def test_qa_gate_luecken_research_runden(board_env, monkeypatch):
+    """Offene Lücken im Auto-Loop: erst LUECKEN_RESEARCH_MAX Recherche-Runden
+    (Lücken-Urteil ausgesetzt), dann das Urteil — erst danach Stillstand/Pause."""
+    import qa as qa_mod
+    import repair as repair_mod
+    db, ctx, files = board_env
+    gap_report = {"note": 8.0, "topic": TOPIC, "quoten": {}, "fremd": [], "artefakte": {},
+                  "luecken": [{"datei": "f.txt", "abschnitt": 1, "vorschau": "x"}],
+                  "konzept_luecken": []}
+
+    async def bad_qa(topic, llm=False):
+        return dict(gap_report)
+
+    research_calls = []
+
+    async def fake_producer(ctx2, flow, rep):
+        research_calls.append(1)
+        return 1  # Recherche hat Karten erzeugt → Runde gilt als bewegt
+
+    urteile = []
+
+    async def stuck_repair(topic, ebene=None, luecken_urteil=True):
+        urteile.append(luecken_urteil)
+        return {"note": 8.0, "aktionen": 0}
+
+    monkeypatch.setattr(qa_mod, "qa_report", bad_qa)
+    monkeypatch.setattr(qa_mod, "latest_report", lambda t, guide=False: dict(gap_report))
+    monkeypatch.setattr(qa_mod, "_write_report", lambda r: None)
+    monkeypatch.setattr(bi, "_luecken_producer", fake_producer)
+    monkeypatch.setattr(repair_mod, "repair_befunde", stuck_repair)
+    monkeypatch.setattr(bi, "_QA_GATE_POLL", 0.05)
+    await _seed(db)
+    ok = await _run_flow(ctx, files)
+    assert ok
+    assert len(research_calls) == 2                    # LUECKEN_RESEARCH_MAX
+    assert urteile[:2] == [False, False] and urteile[2] is True
+    assert await db.kanban_count(TOPIC, "done_artefact", board="artefacts") == 0  # pausiert
+
+
 async def test_qa_gate_auto_reaches_100(board_env, monkeypatch):
     """Auto an, Repair hebt die Note auf 100 % → Gate öffnet, Board 2 läuft durch."""
     import qa as qa_mod
@@ -997,8 +1030,8 @@ async def test_qa_gate_auto_reaches_100(board_env, monkeypatch):
     async def bad_qa(topic, llm=False):
         return {"note": 8.0, "topic": TOPIC, "quoten": {}, "fremd": [], "artefakte": {}}
 
-    async def good_repair(topic, ebene=None):
+    async def good_repair(topic, ebene=None, luecken_urteil=True):
-        return {"note": 10.0}
+        return {"note": 10.0, "aktionen": 1}
 
     monkeypatch.setattr(qa_mod, "qa_report", bad_qa)
     monkeypatch.setattr(qa_mod, "_write_report", lambda r: None)
@@ -1019,7 +1052,7 @@ async def test_qa_gate_auto_off_pauses(board_env, monkeypatch):
     async def good_qa(topic, llm=False):
         return {"note": 10.0, "topic": TOPIC, "quoten": {}, "fremd": [], "artefakte": {}}
 
-    async def no_repair(topic, ebene=None):
+    async def no_repair(topic, ebene=None, luecken_urteil=True):
         raise AssertionError("Auto aus darf nicht reparieren")
 
     monkeypatch.setattr(qa_mod, "qa_report", good_qa)
@@ -1094,6 +1127,11 @@ def test_qa_view_pausiert_logic(tmp_path, monkeypatch):
     counts = {"inventory": {"done_block": 3}, "artefacts": {"generate": 4}}
     v = bi._qa_view(TOPIC, counts, None)
     assert v["pausiert"] is True and v["note"] == 5.0 and v["befunde"] == ["X", "Y"]
+    # 9.6 lag über QA_GATE_NOTE, pausiert den Auto-Loop aber trotzdem (Gate öffnet nur bei VOLL)
+    (tmp_path / TOPIC / "r1.json").write_text(_json.dumps(
+        {"note": 9.6, "quoten": {}, "fremd": [], "unecht": []}), encoding="utf-8")
+    qa_mod._latest_cache.clear()
+    assert bi._qa_view(TOPIC, counts, None)["pausiert"] is True
     from types import SimpleNamespace
     laufend = SimpleNamespace(state={})
     assert bi._qa_view(TOPIC, counts, laufend)["pausiert"] is False  # Flow läuft noch
@@ -1515,3 +1553,27 @@ async def test_sanierung_anker_und_beschreibung_ok_kein_judge(testdb, tmp_path,
     ctx = GenContext(topic=TOPIC, provider="claude", is_cancelled=lambda: False)
     await bi._name_one(ctx, _mk_flow(tmp_path), {"card_id": "c4", "payload": payload})
     assert (await db.kanban_get_card(TOPIC, B, "c4"))["stage"] == "naming_check"
+
+
+def test_themen_zielband_skaliert_mit_atomzahl():
+    """√n-Band: kleine Themen deutlich unter 15, große über dem alten 18er-Cluster-Cap."""
+    lo30, hi30 = bi._themen_zielband(30)
+    assert lo30 >= 2 and hi30 < 15
+    lo285, hi285 = bi._themen_zielband(285)
+    assert hi285 > 18
+    lo4, hi4 = bi._themen_zielband(4)
+    assert lo4 >= 2 and hi4 > lo4
+    # Monotonie: mehr Items → nie kleineres Band
+    prev = (0, 0)
+    for n in (4, 30, 100, 285, 1000):
+        band = bi._themen_zielband(n)
+        assert band >= prev
+        prev = band
+
+
+def test_gruppierung_prompt_rendert_zielband(tmp_path):
+    """Template↔Call-Site-Vertrag: alle Platzhalter versorgt, Band-String im Prompt."""
+    from pipeline import _prompt
+    p = _prompt("Blocks-Gruppierung", topic="t", candidates="x", list="1. a",
+                out_path=tmp_path / "g.json", theme_lo=4, theme_hi=8, n_items=9)
+    assert "~4–8 themes" in p and "(9 items)" in p

backend/tests/test_e2e_fake.py

@@ -1,7 +1,7 @@
 """E2E über die ECHTE Engine mit Fake-Agenten: kompletter Generierungspfad in Sekunden.
 
 Anders als test_board_inventory (dort sind die Block-Funktionen gefakt) läuft hier alles
-bis run_agent echt — _race, Quorum, Panels, Konsolidierung, Cross-Block, QA-Gate.
+bis run_agent echt — _race, Quorum, Panels, In-Block-Konsolidierung, QA-Gate.
 """
 
 import asyncio

backend/tests/test_events.py

@@ -301,6 +301,33 @@ async def test_events_run_summary_per_board(testdb):
     assert (await db.events_run_summary(TOPIC, "r2"))["agents"]["gesamt"] == 2  # ohne board = alle
 
 
+async def test_latest_board_runs_je_ebene(testdb):
+    """Je Ebene der jüngste Lauf MIT Daten: ein „Nur Artefakte"-Lauf (r2) lässt die
+    Inventar-Anzeige auf r1 stehen; Guide-Läufe (Suffix -g+hex4) haben eine eigene Zeile."""
+    db = testdb
+    assert await db.latest_board_runs(TOPIC) == {"inventory": None, "artefacts": None, "guide": None}
+    db.set_current_run(TOPIC, "20260708-1000-aaaa")  # Voll-Lauf: beide Ebenen
+    await db.add_event(TOPIC, "agent", key="i1", status="ok",
+                       meta={"board": "inventory", "tokens": {"input": 10, "output": 1}})
+    await db.add_event(TOPIC, "agent", key="a1", status="ok", meta={"board": "artefacts"})
+    db.set_current_run(TOPIC, "20260708-1100-bbbb")  # „Nur Artefakte"
+    await db.add_event(TOPIC, "agent", key="a2", status="ok",
+                       meta={"board": "artefacts", "tokens": {"input": 5, "output": 7}})
+    db.set_current_run(TOPIC, "20260708-1200-gabc1")  # Guide (Events untagged)
+    await db.add_event(TOPIC, "agent", key="g1", status="ok",
+                       meta={"tokens": {"input": 3, "output": 4}})
+    latest = await db.latest_board_runs(TOPIC)
+    assert latest["inventory"]["run_id"] == "20260708-1000-aaaa"
+    assert latest["inventory"]["tokens"]["input"] == 10
+    assert latest["artefacts"]["run_id"] == "20260708-1100-bbbb"
+    assert latest["artefacts"]["tokens"]["output"] == 7
+    assert latest["guide"]["run_id"] == "20260708-1200-gabc1"
+    assert latest["guide"]["tokens"]["input"] == 3
+    # aktiv folgt der Registry: nur der Guide-Lauf ist noch der aktuelle
+    assert latest["guide"]["aktiv"] and not latest["inventory"]["aktiv"]
+    db.set_current_run(TOPIC, None)
+
+
 async def test_topic_delete_entfernt_guides_und_kanban(testdb, tmp_path, monkeypatch):
     """DELETE /topics: guides/guide_cards/kanban_cards mitlöschen — GET /topics leitet
     Topics aus guides ab, sonst taucht das gelöschte Topic sofort wieder auf."""
@@ -351,6 +378,7 @@ async def test_runs_endpoint_liefert_bilanz(testdb):
     await db.add_event(TOPIC, "fail", key="inventory:b-1", status="dead", meta={"error": "kaputt"})
     res = await routes.get_runs(TOPIC)
     runs = res["runs"]
+    assert set(res["latest"]) == {"inventory", "artefacts", "guide"}  # je Ebene letzter Lauf mit Daten
     assert len(runs) == 1 and runs[0]["run_id"] == "r1" and runs[0]["aktiv"] is True
     assert runs[0]["agents"]["gesamt"] == 2 and runs[0]["agents"]["timeout"] == 1
     assert runs[0]["tokens"]["output"] == 20

backend/tests/test_finalize.py

@@ -0,0 +1,80 @@
+"""Finalize (board_artefacts._proc_finalize) und blocks-Helfer — Judges gefaked, gegen
+Test-DB. Die In-Block-Konsolidierung lebt seit dem Verschmelzungs-Umbau in
+block_calls._verify_block und wird in tests/test_block_calls.py getestet."""
+
+import blocks
+import board_artefacts as ba
+from kanban import Flow
+from pipeline import GenContext
+
+TOPIC = "finalize"
+
+
+def _ctx():
+    return GenContext(topic=TOPIC, provider="test", is_cancelled=lambda: False)
+
+
+def test_luecken_schnitt_cap():
+    l1 = [f"Aspekt-{k} fehlt" for k in ("eins", "zwei", "drei", "vier", "fünf")]
+    assert blocks._luecken_schnitt(l1, list(l1)) == l1[:3]  # Cap 3
+    assert blocks._luecken_schnitt(["Inline-HTML"], ["Tabellen-Syntax"]) == []
+
+
+def test_neg_set_lemmatisiert():
+    """kein/keine/keinen falten auf einen Stamm; nicht vs. ohne bleiben verschieden."""
+    a = blocks._neg_set("Fehlerverhalten (kein Syntaxfehler)")
+    b = blocks._neg_set("Fehlerverhalten (keine Syntax-Fehlermeldung)")
+    assert a == b == frozenset({"kein"})
+    assert blocks._neg_set("nicht expandiert") != blocks._neg_set("ohne Expansion")
+    assert blocks._neg_set("niemals gerendert") == blocks._neg_set("nie gerendert")
+
+
+async def test_finalize_purges_stale_rows(testdb, tmp_path):
+    """Re-Run-Waisen: Finalize löscht Alt-Fragen/-Artefakte des Blocks vor dem Upsert."""
+    db = testdb
+    await db.upsert_question_pattern(TOPIC, "alpha", "alt-sub", "Alpha", "Alt", "Alte Frage?")
+    await db.put_sub_artifact(TOPIC, "alpha", "alt-sub", "flashcard", "{}", "Alpha", "Alt")
+    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
+    files = {k: tmp_path / f"{k}.json" for k in
+             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
+    card = {"card_id": "alpha", "payload": {
+        "title": "Alpha", "raw": {"Alpha": ["Neu"]}, "facts": {},
+        "sidecar": {"Alpha": [{"title": "Neu", "level": "beginner"}]},
+        "pattern": {"Alpha": [{"subblock": "Neu", "question": "F?"}]},
+        "artefacts": {"flashcard": [{"block": "Alpha", "subblock": "Neu", "front": "F", "back": "B"}]}}}
+    flow = Flow(TOPIC, work_dir=tmp_path)
+    await ba._proc_finalize(_ctx(), flow, files, [card])
+    assert {r["sub_norm"] for r in await db.list_question_pattern(TOPIC)} == {"neu"}
+    assert {(r["sub_norm"], r["type"]) for r in await db.get_sub_artefakte(TOPIC)} == {("neu", "flashcard")}
+
+
+async def test_finalize_defaultet_level_nachzuegler(testdb, tmp_path):
+    """Finalize klassifiziert level-/relevance-lose consensus-Rows (Default advanced/relevant)."""
+    db = testdb
+    await db.put_subblock(TOPIC, "alpha", "nachzuegler", "Alpha", "Nachzügler", status="consensus")
+    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
+    files = {k: tmp_path / f"{k}.json" for k in
+             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
+    card = {"card_id": "alpha", "payload": {"title": "Alpha", "raw": {}, "facts": {},
+                                            "sidecar": {}, "pattern": {}, "artefacts": {}}}
+    await ba._proc_finalize(_ctx(), Flow(TOPIC, work_dir=tmp_path), files, [card])
+    row = next(r for r in await db.list_subblocks(TOPIC, "alpha"))
+    assert row["level"] == "advanced" and row["relevance"] == "relevant"
+
+
+async def test_finalize_loescht_stale_consensus(testdb, tmp_path):
+    """Alt-consensus-Rows, die der Lauf-Sidecar nicht mehr trägt, fliegen raus —
+    variant-Rows bleiben (QA liest die Status). Wurzel der 25 Board-2-losen Waisen."""
+    db = testdb
+    await db.put_subblock(TOPIC, "alpha", "alt-rest", "Alpha", "Alt-Rest", status="consensus")
+    await db.put_subblock(TOPIC, "alpha", "alte-variante", "Alpha", "Alte Variante", status="variant")
+    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
+    files = {k: tmp_path / f"{k}.json" for k in
+             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
+    card = {"card_id": "alpha", "payload": {
+        "title": "Alpha", "raw": {"Alpha": ["Neu"]}, "facts": {},
+        "sidecar": {"Alpha": [{"title": "Neu", "level": "beginner"}]},
+        "pattern": {}, "artefacts": {}}}
+    await ba._proc_finalize(_ctx(), Flow(TOPIC, work_dir=tmp_path), files, [card])
+    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "alpha")}
+    assert rows == {"neu": "consensus", "alte-variante": "variant"}

backend/tests/test_guide_board.py

@@ -427,6 +427,36 @@ async def test_repair_karten_setzt_befundkarten_auf_pruefer(testdb, tmp_path, mo
     assert cards["gamma"]["stage"] == "done"
 
 
+async def test_repair_karten_stil_befunde_direkt_auf_fix(testdb, tmp_path, monkeypatch):
+    """Nur-Stil-Befunde (redundanz/laengen/lesbarkeit) → direkt auf `fix` mit
+    Auftragszeilen im gate_info (KEIN KRITISCH-Präfix → ein Rewrite ohne Re-Prüfer);
+    die Redundanz-Zeile trägt den Cross-Karten-Kontext, den der Prüfer nie sieht."""
+    import json as _json
+    import qa as qa_mod
+    db = testdb
+    monkeypatch.setattr(qa_mod, "QA_DIR", tmp_path / "qa")
+    for n in ("alpha", "beta", "gamma"):
+        await db.upsert_guide_card(TOPIC, FMT, n, n.title())
+        await db.set_guide_card(TOPIC, FMT, n, stage="done", status="ok", md="<!-- section: X -->\nText")
+    tdir = tmp_path / "qa" / TOPIC
+    tdir.mkdir(parents=True)
+    (tdir / "guide-20260705-000001.json").write_text(_json.dumps({
+        "marker_fehlend": [], "fachlich_falsch": ["Gamma"], "ziel_ohne_anker": [],
+        "redundanz": [{"a": "Alpha: gemeinsamer Absatztext", "b": "Beta: gemeinsamer Absatztext"}],
+        "laengen_ausreisser": [{"block": "Beta", "zeichen": 9000, "budget": 3000}],
+        "lesbarkeit": ["Alpha: Sätze kürzen"],
+    }), encoding="utf-8")
+    betroffen = await gb.repair_karten(TOPIC, FMT)
+    assert sorted(betroffen) == ["Alpha", "Beta", "Gamma"]
+    cards = {c["block_norm"]: c for c in await db.list_guide_cards(TOPIC, FMT)}
+    assert cards["gamma"]["stage"] == "pruefer"          # kritisch → Prüfer
+    assert cards["alpha"]["stage"] == cards["beta"]["stage"] == "fix"
+    assert not cards["beta"]["gate_info"].startswith("KRITISCH")
+    assert "BALLAST" in cards["beta"]["gate_info"] and "Alpha" in cards["beta"]["gate_info"]
+    assert "LÄNGE" in cards["beta"]["gate_info"] and "3000" in cards["beta"]["gate_info"]
+    assert "LESBARKEIT: Sätze kürzen" in cards["alpha"]["gate_info"]
+
+
 async def test_fix_failed_behaelt_befunde(testdb, tmp_path, monkeypatch):
     """Scheitert der Fix, dürfen die Prüfer-Befunde nicht stumm verschwinden — sie
     bleiben im gate_info sichtbar (vorher wurde gate_info geleert)."""

backend/tests/test_konsolidierung.py

@@ -1,265 +0,0 @@
-"""Cross-Block-Konsolidierung (board_artefacts._proc_konsolidierung) und Finalize —
-Judges gefaked, gegen Test-DB. Die In-Block-Konsolidierung lebt seit dem Verschmelzungs-
-Umbau in block_calls._verify_block und wird in tests/test_block_calls.py getestet."""
-
-import json
-
-import numpy as np
-
-import blocks
-import board_artefacts as ba
-from kanban import Flow
-from pipeline import FAILED, OK, GenContext
-
-TOPIC = "konsolidierung"
-
-
-def _ctx():
-    return GenContext(topic=TOPIC, provider="test", is_cancelled=lambda: False)
-
-
-def _fake_slot(antworten):
-    """run_single_slot-Fake: pro Judge-Key eine Antwort; schreibt via payload (wie der Engine-Sink)."""
-    calls = []
-
-    async def fake(ctx, label, *, key, prompt, role, capabilities, payload, timeout):
-        calls.append({"key": key, "prompt": prompt})
-        j = key.rsplit("-", 1)[-1]  # "j1"/"j2"
-        antwort = antworten.get(j)
-        if antwort is None:
-            return FAILED, None
-        return OK, payload((0, json.dumps(antwort), ""))
-
-    fake.calls = calls
-    return fake
-
-
-async def _seed_block(db, bnorm, subs):
-    for s in subs:
-        await db.put_subblock(TOPIC, bnorm, blocks._norm_title(s), bnorm.title(), s, status="consensus")
-
-
-def test_luecken_schnitt_cap():
-    l1 = [f"Aspekt-{k} fehlt" for k in ("eins", "zwei", "drei", "vier", "fünf")]
-    assert blocks._luecken_schnitt(l1, list(l1)) == l1[:3]  # Cap 3
-    assert blocks._luecken_schnitt(["Inline-HTML"], ["Tabellen-Syntax"]) == []
-
-
-def test_neg_set_lemmatisiert():
-    """kein/keine/keinen falten auf einen Stamm; nicht vs. ohne bleiben verschieden."""
-    a = blocks._neg_set("Fehlerverhalten (kein Syntaxfehler)")
-    b = blocks._neg_set("Fehlerverhalten (keine Syntax-Fehlermeldung)")
-    assert a == b == frozenset({"kein"})
-    assert blocks._neg_set("nicht expandiert") != blocks._neg_set("ohne Expansion")
-    assert blocks._neg_set("niemals gerendert") == blocks._neg_set("nie gerendert")
-
-
-async def test_finalize_purges_stale_rows(testdb, tmp_path):
-    """Re-Run-Waisen: Finalize löscht Alt-Fragen/-Artefakte des Blocks vor dem Upsert."""
-    db = testdb
-    await db.upsert_question_pattern(TOPIC, "alpha", "alt-sub", "Alpha", "Alt", "Alte Frage?")
-    await db.put_sub_artifact(TOPIC, "alpha", "alt-sub", "flashcard", "{}", "Alpha", "Alt")
-    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
-    files = {k: tmp_path / f"{k}.json" for k in
-             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
-    card = {"card_id": "alpha", "payload": {
-        "title": "Alpha", "raw": {"Alpha": ["Neu"]}, "facts": {},
-        "sidecar": {"Alpha": [{"title": "Neu", "level": "beginner"}]},
-        "pattern": {"Alpha": [{"subblock": "Neu", "question": "F?"}]},
-        "artefacts": {"flashcard": [{"block": "Alpha", "subblock": "Neu", "front": "F", "back": "B"}]}}}
-    flow = Flow(TOPIC, work_dir=tmp_path)
-    await ba._proc_finalize(_ctx(), flow, files, [card])
-    assert {r["sub_norm"] for r in await db.list_question_pattern(TOPIC)} == {"neu"}
-    assert {(r["sub_norm"], r["type"]) for r in await db.get_sub_artefakte(TOPIC)} == {("neu", "flashcard")}
-
-
-# ── Cross-Block ─────────────────────────────────────────────────────────────────────
-
-class _FakeEmb:
-    """Gleicher Text → gleicher Einheitsvektor, sonst orthogonal (cos 1.0 / 0.0)."""
-
-    @staticmethod
-    def available():
-        return True
-
-    @staticmethod
-    def embed_sims(texts):
-        uniq = {t: k for k, t in enumerate(dict.fromkeys(texts))}
-        arr = np.zeros((len(texts), max(len(uniq), 1)))
-        for r, t in enumerate(texts):
-            arr[r, uniq[t]] = 1.0
-        return arr @ arr.T
-
-
-async def _cross_env(db, tmp_path, finalisiert=True):
-    """Zwei finalisierte Karten in der End-Barriere; die Sub-Rows liegen in der DB
-    (post-finalize ist die DB die Wahrheit, nicht mehr das Karten-Payload)."""
-    flow = Flow(TOPIC, work_dir=tmp_path)
-    cards = []
-    for bnorm, subs in (("alpha", ["Gleiche Aussage", "Nur in Alpha"]),
-                        ("beta", ["Gleiche Aussage", "Nur in Beta"])):
-        payload = {"title": bnorm.title()}
-        if finalisiert:
-            payload.update(pattern={}, artefacts={})
-        await db.kanban_upsert_card(TOPIC, "artefacts", bnorm, "ablock", "konsolidierung", payload)
-        await _seed_block(db, bnorm, subs)
-        cards.append({"card_id": bnorm, "payload": payload})
-    files = {k: tmp_path / f"{k}.json" for k in
-             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
-    return flow, cards, files
-
-
-async def test_crossblock_folds_loser(testdb, tmp_path, monkeypatch):
-    """Einstimmig „a" → Betas geteilte Aussage wird variant, ihre Frage wandert zum
-    Gewinner (falte_sub), Karten gehen auf DONE."""
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path)
-    sn = blocks._norm_title("Gleiche Aussage")
-    await db.upsert_question_pattern(TOPIC, "beta", sn, "Beta", "Gleiche Aussage", "F?")
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    fake = _fake_slot({"j1": {"pairs": {"1": "a"}}, "j2": {"pairs": {"1": "a"}}})
-    monkeypatch.setattr(ba, "run_single_slot", fake)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    assert "Gleiche Aussage" in fake.calls[0]["prompt"]
-    for cid in ("alpha", "beta"):
-        assert (await db.kanban_get_card(TOPIC, "artefacts", cid))["stage"] == ba.DONE
-    beta_rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert beta_rows[sn] == "variant"
-    alpha_rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "alpha")}
-    assert alpha_rows[sn] == "consensus"
-    fragen = await db.list_question_pattern(TOPIC)
-    assert {(r["block_norm"], r["sub_norm"]) for r in fragen} == {("alpha", sn)}  # umgehängt
-
-
-async def test_crossblock_tiebreaker_folds(testdb, tmp_path, monkeypatch):
-    """j1/j2 uneinig → j3 entscheidet mit Mehrheit; hier „a" → Beta verliert."""
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path)
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    fake = _fake_slot({"j1": {"pairs": {"1": "a"}}, "j2": {"pairs": {"1": "nein"}},
-                       "j3": {"pairs": {"1": "a"}}})
-    monkeypatch.setattr(ba, "run_single_slot", fake)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    assert len(fake.calls) == 3
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert rows[blocks._norm_title("Gleiche Aussage")] == "variant"
-
-
-async def test_crossblock_dissent_without_tiebreaker_keeps_both(testdb, tmp_path, monkeypatch):
-    """j3 liefert nichts (FAILED) → fail-open, Paar bleibt."""
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path)
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    fake = _fake_slot({"j1": {"pairs": {"1": "a"}}, "j2": {"pairs": {"1": "b"}}})  # j3 fehlt → FAILED
-    monkeypatch.setattr(ba, "run_single_slot", fake)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    assert (await db.kanban_get_card(TOPIC, "artefacts", "beta"))["stage"] == ba.DONE
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert rows[blocks._norm_title("Gleiche Aussage")] == "consensus"
-
-
-async def test_crossblock_ersatzrichter(testdb, tmp_path, monkeypatch):
-    """Nur ein Richter liefert → Ersatz jE als zweite Stimme; Einstimmigkeit faltet."""
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path)
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    fake = _fake_slot({"j1": {"pairs": {"1": "a"}}, "jE": {"pairs": {"1": "a"}}})  # j2 → FAILED
-    monkeypatch.setattr(ba, "run_single_slot", fake)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert rows[blocks._norm_title("Gleiche Aussage")] == "variant"
-
-
-async def test_crossblock_without_embedding_advances(testdb, tmp_path, monkeypatch):
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path)
-
-    class _Aus:
-        @staticmethod
-        def available():
-            return False
-
-    async def kein_agent(*a, **kw):
-        raise AssertionError("ohne Embedding kein Judge")
-
-    monkeypatch.setattr(ba, "embedding", _Aus)
-    monkeypatch.setattr(ba, "run_single_slot", kein_agent)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    for cid in ("alpha", "beta"):
-        assert (await db.kanban_get_card(TOPIC, "artefacts", cid))["stage"] == ba.DONE
-
-
-async def test_crossblock_nachzuegler_zurueck_zum_erzeugen(testdb, tmp_path, monkeypatch):
-    """Resume-Karte ohne pattern im Payload → zurück nach generate (bzw. artefakte bei
-    vorhandenem sidecar), KEIN Dedup — finalize würde den Fold sonst re-spiegeln."""
-    db = testdb
-    flow, cards, files = await _cross_env(db, tmp_path, finalisiert=False)
-    cards[1]["payload"]["sidecar"] = {"Beta": []}  # hat Verify schon hinter sich
-    await db.kanban_set_payload(TOPIC, "artefacts", "beta", cards[1]["payload"])
-
-    async def kein_agent(*a, **kw):
-        raise AssertionError("Nachzügler dürfen keinen Dedup auslösen")
-
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    monkeypatch.setattr(ba, "run_single_slot", kein_agent)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    assert (await db.kanban_get_card(TOPIC, "artefacts", "alpha"))["stage"] == "generate"
-    assert (await db.kanban_get_card(TOPIC, "artefacts", "beta"))["stage"] == "artefakte"
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert rows[blocks._norm_title("Gleiche Aussage")] == "consensus"
-
-
-async def test_finalize_defaultet_level_nachzuegler(testdb, tmp_path):
-    """Finalize klassifiziert level-/relevance-lose consensus-Rows (Default advanced/relevant)."""
-    db = testdb
-    await db.put_subblock(TOPIC, "alpha", "nachzuegler", "Alpha", "Nachzügler", status="consensus")
-    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
-    files = {k: tmp_path / f"{k}.json" for k in
-             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
-    card = {"card_id": "alpha", "payload": {"title": "Alpha", "raw": {}, "facts": {},
-                                            "sidecar": {}, "pattern": {}, "artefacts": {}}}
-    await ba._proc_finalize(_ctx(), Flow(TOPIC, work_dir=tmp_path), files, [card])
-    row = next(r for r in await db.list_subblocks(TOPIC, "alpha"))
-    assert row["level"] == "advanced" and row["relevance"] == "relevant"
-
-
-async def test_finalize_loescht_stale_consensus(testdb, tmp_path):
-    """Alt-consensus-Rows, die der Lauf-Sidecar nicht mehr trägt, fliegen raus —
-    variant-Rows bleiben (QA liest die Status). Wurzel der 25 Board-2-losen Waisen."""
-    db = testdb
-    await db.put_subblock(TOPIC, "alpha", "alt-rest", "Alpha", "Alt-Rest", status="consensus")
-    await db.put_subblock(TOPIC, "alpha", "alte-variante", "Alpha", "Alte Variante", status="variant")
-    await db.kanban_upsert_card(TOPIC, "artefacts", "alpha", "ablock", "finalize", {})
-    files = {k: tmp_path / f"{k}.json" for k in
-             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
-    card = {"card_id": "alpha", "payload": {
-        "title": "Alpha", "raw": {"Alpha": ["Neu"]}, "facts": {},
-        "sidecar": {"Alpha": [{"title": "Neu", "level": "beginner"}]},
-        "pattern": {}, "artefacts": {}}}
-    await ba._proc_finalize(_ctx(), Flow(TOPIC, work_dir=tmp_path), files, [card])
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "alpha")}
-    assert rows == {"neu": "consensus", "alte-variante": "variant"}
-
-
-async def test_crossblock_chunking_faltet_global(testdb, tmp_path, monkeypatch):
-    """Paare werden gechunkt beurteilt (ein Hänger blockiert nur noch seinen Chunk);
-    die Verdicts falten global über alle Chunks."""
-    db = testdb
-    flow = Flow(TOPIC, work_dir=tmp_path)
-    cards = []
-    for bnorm, subs in (("alpha", ["Gleiche Aussage", "Zweite gleiche Aussage", "Nur in Alpha"]),
-                        ("beta", ["Gleiche Aussage", "Zweite gleiche Aussage"])):
-        payload = {"title": bnorm.title(), "pattern": {}, "artefacts": {}}
-        await db.kanban_upsert_card(TOPIC, "artefacts", bnorm, "ablock", "konsolidierung", payload)
-        await _seed_block(db, bnorm, subs)
-        cards.append({"card_id": bnorm, "payload": payload})
-    files = {k: tmp_path / f"{k}.json" for k in
-             ("sub_roh", "facts", "sidecar", "question_pattern", "artefakte")}
-    monkeypatch.setattr(ba, "embedding", _FakeEmb)
-    monkeypatch.setattr(ba, "CROSS_CHUNK_PAARE", 1)  # 2 Paare → 2 Chunks
-    fake = _fake_slot({"j1": {"pairs": {"1": "a"}}, "j2": {"pairs": {"1": "a"}}})
-    monkeypatch.setattr(ba, "run_single_slot", fake)
-    await ba._proc_konsolidierung(_ctx(), flow, files, "", cards)
-    assert len(fake.calls) == 4  # 2 Chunks × j1/j2
-    rows = {r["sub_norm"]: r["status"] for r in await db.list_subblocks(TOPIC, "beta")}
-    assert set(rows.values()) == {"variant"}  # beide Dubletten global gefaltet

backend/tests/test_pdf_convert.py

@@ -26,6 +26,7 @@ def test_convert_writes_markdown_txt(tmp_path):
 
 def test_cache_skips_fresh_txt(tmp_path):
     _mini_pdf(tmp_path / "a.pdf")
+    (tmp_path / ".pdf-txt-norm").write_text(str(blx._PDF_NORM_VERSION), encoding="utf-8")
     marker = tmp_path / "a.txt"
     marker.write_text("MARKER", encoding="utf-8")
     now = time.time() + 60
@@ -34,6 +35,39 @@ def test_cache_skips_fresh_txt(tmp_path):
     assert marker.read_text(encoding="utf-8") == "MARKER"  # nicht neu konvertiert
 
 
+def test_norm_version_erzwingt_rekonvertierung(tmp_path, monkeypatch):
+    """Fehlender/alter .pdf-txt-norm-Marker ignoriert den mtime-Cache einmalig."""
+    _mini_pdf(tmp_path / "a.pdf")
+    stale = tmp_path / "a.txt"
+    stale.write_text("ALT", encoding="utf-8")
+    now = time.time() + 60
+    os.utime(stale, (now, now))
+    monkeypatch.setattr(blx, "_pdf_markdown", lambda p: None)
+    monkeypatch.setattr(blx, "_pdf_plaintext", lambda p: "neu konvertiert")
+    blx._convert_pdfs(tmp_path)
+    assert stale.read_text(encoding="utf-8") == "neu konvertiert"
+    assert (tmp_path / ".pdf-txt-norm").read_text(encoding="utf-8") == str(blx._PDF_NORM_VERSION)
+    stale.write_text("BLEIBT", encoding="utf-8")
+    os.utime(stale, (now, now))
+    blx._convert_pdfs(tmp_path)  # Marker aktuell → Cache greift wieder
+    assert stale.read_text(encoding="utf-8") == "BLEIBT"
+
+
+def test_entzerre_pdf_woerter():
+    """Small-Caps-Splits mergen; Variablen-Schutzfall und unbelegte Paare bleiben."""
+    # Regel A inkl. Kette
+    assert blx._entzerre_pdf_woerter("Das H ITTING S ET Problem") == "Das HITTING SET Problem"
+    assert blx._entzerre_pdf_woerter("V ERTEX C OVER ist schwer") == "VERTEX COVER ist schwer"
+    # Schutzfall: Großlauf klein fortgesetzt → L ist Variable
+    assert blx._entzerre_pdf_woerter("die Sprache L NP-vollständig ist") == "die Sprache L NP-vollständig ist"
+    # Regel B: Paar nur mit Frequenz-Beleg (≥3× ungespalten im Dokument)
+    belegt = "N P ist zentral. " + "NP NP NP."
+    assert blx._entzerre_pdf_woerter(belegt).startswith("NP ist zentral.")
+    assert blx._entzerre_pdf_woerter("C Y bleibt getrennt") == "C Y bleibt getrennt"
+    # kein Match mitten im Wort
+    assert blx._entzerre_pdf_woerter("HALTTM IST hier") == "HALTTM IST hier"
+
+
 def test_fallback_to_pdftotext(tmp_path, monkeypatch):
     _mini_pdf(tmp_path / "b.pdf")
     monkeypatch.setattr(blx, "_pdf_markdown", lambda p: None)

backend/tests/test_qa.py

@@ -313,3 +313,23 @@ async def test_topic_delete_entfernt_qa_ordner(testdb, tmp_path, monkeypatch):
     (qdir / "alt.json").write_text("{}", encoding="utf-8")
     await routes.remove_topic("t")
     assert not qdir.exists()
+
+
+def test_luecken_key_stabil_gegen_whitespace():
+    """Freispruch-Schlüssel: Datei + normalisierter Vorschau-Hash — Whitespace-Varianten
+    derselben Fundstelle mappen auf denselben Key, andere Vorschau nicht."""
+    a = {"datei": "f.txt", "abschnitt": 3, "vorschau": "Der  Satz\nvon Foo"}
+    b = {"datei": "f.txt", "abschnitt": 7, "vorschau": "der satz von foo"}
+    c = {"datei": "f.txt", "abschnitt": 3, "vorschau": "ganz anderer Text"}
+    assert qa.luecken_key(a) == qa.luecken_key(b)
+    assert qa.luecken_key(a) != qa.luecken_key(c)
+    assert qa.luecken_key(a).startswith("f.txt||")
+
+
+def test_offene_luecken_filtert_freispruch_und_nein():
+    rep = {"luecken": [{"datei": "f", "vorschau": "a", "llm": "ja"},
+                       {"datei": "f", "vorschau": "b", "llm": "nein"},
+                       {"datei": "f", "vorschau": "c", "freispruch": True}],
+           "konzept_luecken": ["Satz von Foo"]}
+    lk, kl = qa.offene_luecken(rep)
+    assert [x["vorschau"] for x in lk] == ["a"] and kl == ["Satz von Foo"]

backend/tests/test_repair.py

@@ -298,3 +298,135 @@ async def test_waisen_cleanup(env, monkeypatch):
     rest = {(r["sub_norm"], r["type"]) for r in await db.get_sub_artefakte(TOPIC)}
     assert rest == {("sub0", "flashcard"), ("doppel", "example")}
     assert not [r for r in await db.list_question_pattern(TOPIC)]
+
+
+async def test_dubletten_verdacht_freispruch(env, monkeypatch):
+    """Widerlegtes/unbeurteiltes Verdachtspaar bekommt den Klärungskanal: Judge sagt
+    behalten → Freispruch persistiert; der nächste qa_report zählt das Paar nicht mehr
+    (vorher zählte widerlegter Verdacht ewig in die Quote — Mess-Rauschen ohne Ausweg)."""
+    import qa as qa_mod
+    db, seed, files, write_report = env
+    await seed("Alpha", "beschr")
+    await seed("Alpha Kreis", "beschr")
+    write_report(_report(dubletten=[{"a": "Alpha", "b": "Alpha Kreis", "llm": "nein"}]))
+
+    async def fake_agent(key, prompt, timeout, **kw):
+        return 0, '{"relevant": {"1": "nein"}}', ""  # Judge: keine Dublette
+
+    import agents; monkeypatch.setattr(agents, "run_agent", fake_agent)
+    res = await repair.repair_befunde(TOPIC)
+    assert res["merges"] == [] and len(res["freigesprochen"]) == 1 and res["aktionen"] == 1
+    frei = qa_mod.lade_freispruch(TOPIC)
+    assert qa_mod._paar_key("Alpha", "Alpha Kreis") in set(frei.get("dubletten") or [])
+
+
+async def test_dubletten_verdacht_stichentscheid_merged(env, monkeypatch):
+    """Verdachtspaar (llm=nein), aber Judge+Stichentscheid sagen beide Dublette →
+    Merge mit 2:1 gegen das QA-Urteil."""
+    db, seed, files, write_report = env
+    await seed("Alpha", "kurz")
+    await seed("Alpha Kreis", "deutlich längere Beschreibung — Gewinner")
+    write_report(_report(dubletten=[{"a": "Alpha", "b": "Alpha Kreis", "llm": "nein"}]))
+
+    async def fake_agent(key, prompt, timeout, **kw):
+        return 0, '{"relevant": {"1": "ja"}}', ""
+
+    import agents; monkeypatch.setattr(agents, "run_agent", fake_agent)
+    res = await repair.repair_befunde(TOPIC)
+    assert res["merges"] == ["Alpha → Alpha Kreis"] and res["freigesprochen"] == []
+
+
+async def test_beleg_nachfass_discard_und_datenfix(env, monkeypatch):
+    """mentions=0-Subs: Judge bestätigt „kein Beleg" → Sub verworfen; Dissens mit
+    Stichentscheid „belegt" → mentions=1 nachgetragen (Datenfix, kein Freispruch)."""
+    db, seed, files, write_report = env
+    await seed("Alpha", "beschr")
+    norm = repair._norm_title("Alpha")
+    await db.put_subblock(TOPIC, norm, "ohne beleg", "Alpha", "Ohne Beleg", status="consensus")
+    await db.put_subblock(TOPIC, norm, "doch belegt", "Alpha", "Doch Belegt", status="consensus")
+    await db.set_subblock_fields(TOPIC, norm, "ohne beleg", mentions=0)
+    await db.set_subblock_fields(TOPIC, norm, "doch belegt", mentions=0)
+    write_report(_report(beleg={"subs_ohne_beleg": ["Alpha · Ohne Beleg", "Alpha · Doch Belegt"]}))
+    monkeypatch.setattr(repair, "source_folder", lambda t: files["sidecar"].parent)
+    monkeypatch.setattr(repair, "_evidence_pack", lambda *a, **kw: "AUSZUG")
+
+    async def fake_agent(key, prompt, timeout, **kw):
+        if "-beleg-st-" in key:
+            return 0, '{"relevant": {"1": "ja"}}', ""   # Stichentscheid: belegt
+        return 0, '{"relevant": {"1": "nein", "2": "ja"}}', ""
+
+    import agents; monkeypatch.setattr(agents, "run_agent", fake_agent)
+    res = await repair.repair_befunde(TOPIC, "artefacts")
+    assert sorted(res["beleg_fix"]) == ["belegt: Alpha · Doch Belegt", "entfernt: Alpha · Ohne Beleg"]
+    rows = {r["sub_norm"]: r for r in await db.list_subblocks(TOPIC, norm)}
+    assert rows["ohne beleg"]["status"] == "discarded"
+    assert rows["doch belegt"]["status"] == "consensus" and rows["doch belegt"]["mentions"] == 1
+
+
+async def test_fix_beschreibung_fuellt_leere(env, monkeypatch):
+    """Hygiene „leere-beschreibung" → Sanierung schreibt EINE Beschreibung aus den
+    Auszügen; Titel bleibt unverändert."""
+    db, seed, files, write_report = env
+    cid = await seed("Leerling", "")
+    write_report(_report(hygiene=[{"titel": "Leerling", "probleme": ["leere-beschreibung"]}]))
+    monkeypatch.setattr(repair, "source_folder", lambda t: files["sidecar"].parent)
+    monkeypatch.setattr(repair, "_evidence_pack", lambda *a, **kw: "AUSZUG")
+
+    async def fake_agent(key, prompt, timeout, **kw):
+        assert "-sanierung-" in key
+        return 0, '{"title": "Leerling", "description": "Aus dem Material."}', ""
+
+    import agents; monkeypatch.setattr(agents, "run_agent", fake_agent)
+    res = await repair.repair_befunde(TOPIC, "inventory")
+    assert "beschrieben: Leerling" in res["hygiene"]
+    card = await db.kanban_get_card(TOPIC, "inventory", cid)
+    assert card["payload"]["description"] == "Aus dem Material."
+
+
+async def test_fix_suffix_rename_rekeyt_alles(env, monkeypatch):
+    """Kollisions-Suffix, Basis-Norm frei → Rename inkl. Re-Key von Subblocks/Fragen/
+    Artefakten + Board-2-Karte; danach keine Invarianten-Waisen."""
+    from invarianten import pruefe_invarianten
+    db, seed, files, write_report = env
+    cid = await seed("Gamma (2)", "beschr")
+    norm_alt = repair._norm_title("Gamma (2)")
+    await db.upsert_question_pattern(TOPIC, norm_alt, "sub0", "Gamma (2)", "Sub 0", "F?")
+    write_report(_report(hygiene=[{"titel": "Gamma (2)", "probleme": ["kollisions-suffix"]}]))
+
+    async def no_agent(*a, **kw):
+        raise AssertionError("Rename bei freier Basis braucht keinen Agenten")
+
+    import agents; monkeypatch.setattr(agents, "run_agent", no_agent)
+    res = await repair.repair_befunde(TOPIC, "inventory")
+    assert "suffix: Gamma (2) → Gamma" in res["hygiene"]
+    card = await db.kanban_get_card(TOPIC, "inventory", cid)
+    assert card["payload"]["title"] == "Gamma" and card["payload"]["mirrored_norm"] == "gamma"
+    assert await db.kanban_get_card(TOPIC, "artefacts", norm_alt) is None
+    assert (await db.kanban_get_card(TOPIC, "artefacts", "gamma"))["payload"]["title"] == "Gamma"
+    assert {r["block_norm"] for r in await db.list_subblocks(TOPIC, "gamma")} == {"gamma"}
+    assert not await db.list_subblocks(TOPIC, norm_alt)
+    assert {r["block_norm"] for r in await db.list_question_pattern(TOPIC)} == {"gamma"}
+    befunde = await pruefe_invarianten(TOPIC)  # DB-Sicht: keine Waisen nach dem Re-Key
+    assert not [b for b in befunde if "Waise" in b]
+
+
+async def test_pruefe_luecken_freispruch(env, monkeypatch):
+    """Offene Lücken + Konzept-Lücken: 2:1 „keine echte Lücke" → Freispruch persistiert;
+    _zaehlbare_luecken zählt freigesprochene Fundstellen nicht mehr."""
+    import qa as qa_mod
+    db, seed, files, write_report = env
+    await seed("Alpha", "beschr")
+    lk = [{"datei": "f.txt", "abschnitt": 1, "vorschau": "verwaister Abschnitt", "llm": "ja"}]
+    write_report(_report(luecken=lk, konzept_luecken=["Satz von Foo"]))
+
+    async def fake_agent(key, prompt, timeout, **kw):
+        return 0, '{"relevant": {"1": "nein"}}', ""  # beide Judges: keine echte Lücke
+
+    import agents; monkeypatch.setattr(agents, "run_agent", fake_agent)
+    res = await repair.repair_befunde(TOPIC, "inventory")
+    assert len(res["freigesprochen"]) == 2
+    frei = qa_mod.lade_freispruch(TOPIC)
+    assert qa_mod.luecken_key(lk[0]) in set(frei.get("luecken") or [])
+    assert "satz von foo" in {s.casefold() for s in frei.get("konzept_luecken") or []}
+    lk[0]["freispruch"] = True
+    assert qa_mod._zaehlbare_luecken(lk, llm=True) == []

backend/train_params.py

@@ -27,7 +27,7 @@ PARAMS: dict[str, dict] = {
     "SEED_COVER_COS":         {"default": 0.80, "min": 0.7,  "max": 0.9,  "step": 0.02, "kategorie": "auswahl", "fidelity": "board2"},
     "SUB_DUP_KANDIDAT_COS":   {"default": 0.75, "min": 0.65, "max": 0.85, "step": 0.02, "kategorie": "auswahl", "fidelity": "board2"},
     "EMBEDDING_BLOCK_FLOOR":  {"default": 0.5,  "min": 0.35, "max": 0.65, "step": 0.05, "kategorie": "auswahl", "fidelity": "voll"},
-    "CROSS_CHUNK_PAARE":      {"default": 40,   "min": 15,   "max": 80,   "step": 10,   "kategorie": "laufzeit", "fidelity": "board2"},
+    "GROUP_THEMES_PER_SQRT":  {"default": 1.0,  "min": 0.6,  "max": 1.6,  "step": 0.2,  "kategorie": "auswahl", "fidelity": "voll"},
     # Guide
     "GATE_FIX_MIN":           {"default": 3,    "min": 1,    "max": 6,    "step": 1,    "kategorie": "qualitaet", "fidelity": "board2"},
     "WRITER_SPLIT_SUBS":      {"default": 30,   "min": 15,   "max": 45,   "step": 5,    "kategorie": "qualitaet", "fidelity": "board2"},

frontend/src/components/GenerationView.vue

@@ -69,33 +69,36 @@ const pct = (note) => Math.round(note * 10) + ' %'
 
 // ── Laufzeit + Tokens aus /api/runs (5s-Takt, unabhängig vom 1,2s-Board-Poll) ──────
 const run = ref(null)
+const latest = ref(null)  // jüngster Lauf MIT Daten je Ebene — überlebt „Nur Artefakte"-Läufe
 const now = ref(Date.now())
 let clock = null
 async function loadRun() {
   try {
-    const { runs } = await fetchRuns(props.topic, 1)
+    const res = await fetchRuns(props.topic, 1)
-    run.value = runs[0] || null
+    run.value = res.runs[0] || null
-  } catch { run.value = null }
+    latest.value = res.latest || null
+  } catch { run.value = null; latest.value = null }
 }
 const { start: startRunPoll } = usePolling(loadRun, () => props.generating, 5000)
-// Per-Ebene: Zeit + Tokens getrennt für Inventar vs. Artefakte (aus run.boards).
+// Per-Ebene: Zeit + Tokens getrennt für Inventar vs. Artefakte. Live tickt nur die Ebene,
+// deren Lauf der AKTUELLE ist (b.aktiv) — sonst zählt die alte Inventar-Zeile mit hoch.
 function boardZeit(b) {
   if (!b?.start) return null
   const start = Date.parse(b.start)
-  const ende = run.value?.aktiv ? now.value : Date.parse(b.ende || b.start)
+  const ende = b.aktiv ? now.value : Date.parse(b.ende || b.start)
   return fmtRuntime((ende - start) / 1000)
 }
 function boardTokens(b) {
   const t = b?.tokens
   return t && (t.input || t.output) ? fmtTokens((t.input || 0) + (t.output || 0)) : null
 }
-const invStat = computed(() => run.value?.boards?.inventory)
+const invStat = computed(() => latest.value?.inventory)
-const artStat = computed(() => run.value?.boards?.artefacts)
+const artStat = computed(() => latest.value?.artefacts)
 watch(() => props.generating, (g) => {
   if (g) { startRunPoll(); if (!clock) clock = setInterval(() => { now.value = Date.now() }, 1000) }
   else { loadRun(); if (clock) { clearInterval(clock); clock = null } }  // Endstand
 }, { immediate: true })
-watch(() => props.topic, () => { run.value = null; loadRun() })
+watch(() => props.topic, () => { run.value = null; latest.value = null; loadRun() })
 onUnmounted(() => { if (clock) clearInterval(clock) })
 
 const { isArmed, armOrRun, reset: resetConfirm } = useConfirm()  // 2-Klick-Bestätigung
@@ -134,7 +137,7 @@ async function repairClick(ebene) {
       const suffix = max > 1 ? ` — Runde ${i + 1}${note != null ? ` (${Math.round(note * 10)} %)` : ''}` : ''
       repairInfo.value = { ...repairInfo.value, [ebene]: repairText(r) + suffix }
       if (note == null || note >= 10) break          // 100 % erreicht
-      if (prev != null && note <= prev) break         // Stillstand: Repair bewegt nichts mehr
+      if (r.aktionen === 0 && prev != null && note <= prev) break // Stillstand: nichts getan, Note steht
       prev = note
     }
   } catch (e) {

frontend/src/components/GuideBoardSection.vue

@@ -41,14 +41,14 @@ const progressValue = computed(() => (total.value ? done.value / total.value : 0
 // QA-Badge nur wenn es ein Board gibt — sonst zeigt ein verwaister Report eine alte Note.
 const qaNote = computed(() => (total.value ? board.value?.qa_guide : null))
 
-// Laufzeit + Tokens aus /api/runs (deckt auch Guide-Läufe ab — beide setzen run_id)
+// Laufzeit + Tokens aus /api/runs — `latest.guide` ist der jüngste GUIDE-Lauf
+// (der jüngste Lauf insgesamt kann ein Blocks-Lauf sein und zeigte hier dessen Zahlen).
 const run = ref(null)
 const now = ref(Date.now())
 let clock = null
 async function loadRun() {
   try {
-    const { runs } = await fetchRuns(props.topic, 1)
+    run.value = (await fetchRuns(props.topic, 1)).latest?.guide || null
-    run.value = runs[0] || null
   } catch { run.value = null }
 }
 const { start: startRunPoll } = usePolling(loadRun, () => generating.value, 5000)

templates/Prompt/Blocks-Gruppierung.md

@@ -1,6 +1,6 @@
 Topic "{topic}". A previous step produced a flat list of learning items that is TOO FINE-GRAINED for a table of contents — single environment variables, single CLI flags, single config fields, near-synonyms. Your job is **card sorting**: group the items into a small set of **theme blocks**, so that EVERY item lands in exactly one theme. Nothing is discarded — grouping never loses an item; it only organises them.
 
-Think of the result as chapters: ~15–25 themes for a whole topic, each a coherent learning block that a learner meets as one unit. A theme with only one fitting item is fine (a genuinely standalone concept), but prefer pulling related items together over leaving many singletons.
+Think of the result as chapters: ~{theme_lo}–{theme_hi} themes for a whole topic of this size ({n_items} items), each a coherent learning block that a learner meets as one unit. A theme with only one fitting item is fine (a genuinely standalone concept), but prefer pulling related items together over leaving many singletons.
 
 CANDIDATES you may group (your starting point — a pre-clustered neighbourhood):
 {candidates}

templates/Prompt/Blocks-Luecken-Research.md

@@ -0,0 +1,20 @@
+Topic "{topic}". A quality audit found GAPS: source-material passages and named results that NO existing inventory block covers. Your job: propose new learning blocks ONLY for these gaps — nothing else. An empty list is a valid answer (when the gaps are filler or already covered under another name).
+
+EXISTING BLOCKS (do NOT re-propose these or near-synonyms of them):
+{blocks}
+
+UNCOVERED MATERIAL (gap passages and named results, with source excerpts):
+{gaps}
+
+Rules:
+- One block per genuinely missing, teachable concept — self-contained, exam-relevant.
+- Ground every proposal in the material above; never invent canon knowledge the material does not treat.
+- Title: concrete concept name (max 8 words, no catalog references like "(Satz 6.33)").
+- Description: ONE sentence naming what the block teaches, grounded in the material.
+- Skip organizational text, prefaces, exercise scaffolding, duplicates of existing blocks.
+
+Write ONLY the JSON file to: {out_path}
+
+Format (`blocks` may be empty):
+{{"blocks": [{{"title": "…", "description": "…"}}]}}
+{extra}

templates/Prompt/Subblock-Crossblock.md

@@ -1,13 +0,0 @@
-Das Lernbaustein-Inventar zum Thema "{topic}" ist in Blöcke mit je eigenen Subbausteinen zerlegt. Manche Aussage taucht in ZWEI Blöcken auf — im Lernguide steht sie dann doppelt. Für jedes Paar unten: Treffen A und B DIESELBE Aussage?
-
-PAARE (jeweils mit Block-Zugehörigkeit und Kernpunkten):
-{pairs}
-
-## Entscheidung pro Paar
-- **DIESELBE Aussage** (auch anders formuliert, oder eine ist Teilmenge der anderen): Welcher Block ist die natürliche Heimat der Aussage? → antworte **"a"** (A behält sie, B verliert sie) oder **"b"** (B behält sie, A verliert sie). Heimat ist der Block, in dessen Kernthema die Aussage gehört — nicht der, der sie nur am Rand streift.
-- **VERSCHIEDENE Aussagen** → antworte **"nein"**. Dazu zählt: gleiche Regel, aber auf VERSCHIEDENE Kontexte angewendet (die Anwendung im jeweiligen Block-Kontext ist eigener Lernstoff); Grundregel vs. Sonderfall; gegensätzliche Aussagen.
-- Im Zweifel: **"nein"**.
-
-Antworte NUR mit JSON, ohne weiteren Text (jede Paar-Nummer mit "a", "b" oder "nein"):
-{{"pairs": {{"1": "a", "2": "nein"}}}}
-{extra}

templates/QA/QA-Konzept-Luecken.md

@@ -0,0 +1,15 @@
+You are an INDEPENDENT quality auditor for a learning-block inventory on the topic "{topic}". Below are NAMED results/concepts a scan found in the source material (named theorems, algorithms, definitions) that seem to map to NO inventory block. For each: is this a real, exam-relevant concept the inventory is missing → **ja**, or is it covered by an existing block under another name / a mangled-extraction artefact / mere organizational labeling → **nein**?
+
+NAMED RESULTS WITHOUT A COVERING BLOCK:
+{results}
+
+Rules:
+- Covered by an existing block under a synonym, symbol variant or broader umbrella → nein.
+- Garbled extraction artefacts (split or shredded words) and pure numbering references → nein.
+- A genuine named result the material teaches and no block captures → ja.
+- When genuinely unsure → ja (a missed gap is worse than one extra research round).
+
+Reply with ONLY the JSON — no other text, no code fences.
+Format (one verdict per number):
+{{"relevant": {{"1": "ja", "2": "nein"}}}}
+{extra}