feat(profile+report): P17 — 4 Polish-Items
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A) Cookie-Policy-Architecture-Block Fallback auf DSE-Text wenn cookie via P15 deduped wurde. Erkennt jetzt auch single-doc Sites (Safetykon-Pattern). B) Konkrete-Aufgaben-Liste: Per-Doc-Cap (3) entfernt + globaler Cap 10→20. Safetykon zeigt jetzt 7 statt 4 Aufgaben. C) business_type-Klassifizierer: B2B-Service-Cluster aus P14 als Boost. Bei 2+ Service-Indikatoren (CE-Zertifizierung/Compliance/Auditierung) wird b2b_score angehoben. Safetykon: "B2C consulting" → "B2B (consulting)". D) Vendor-Extract Fallback auf DSE-Text wenn cookie deduped + keine CMP- Payloads. LLM extrahiert dann Vendors aus dem DSE-Text. Safetykon: 0 → 1 Vendor (Google Analytics aus dem DSE-Text erkannt). Smoke-Test Safetykon: alle 4 Polish-Items wirken, kein Regression. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -237,6 +237,13 @@ async def detect_business_profile(documents: dict[str, str]) -> BusinessProfile:
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b2g_score = _count_hits(full_text, _B2G_KEYWORDS)
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nonprofit_score = _count_hits(full_text, _NONPROFIT_KEYWORDS)
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# P17-C: B2B-Dienstleister-Cluster (P14) als Boost — wenn ein Unternehmen
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# CE-Zertifizierung / Compliance-Beratung / Auditierung / Schulungen anbietet,
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# ist es i.d.R. B2B auch wenn die strikten B2B-Keywords nicht greifen.
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b2b_service_boost = _count_hits(full_text, _B2B_SERVICE_POSITIVE)
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if b2b_service_boost >= 2:
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b2b_score += min(3, b2b_service_boost - 1)
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# Missing documents as signal
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has_agb = "agb" in documents
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has_widerruf = "widerruf" in documents
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