feat(agents): Specialist-Agents Phase 2 Foundation + Cookie-Policy-Agent
Sprint 1 — Foundation (User-Vorgabe 2026-06-08): Foundation: - _base.py: BaseSpecialistAgent ABC + Pydantic Contract (AgentInput/AgentOutput/Finding/Recommendation/McCoverage/EscalationLog). - _base.lint_output(): Disclaimer-Linter verbietet "rechtssicher" / "garantiert" / "gesetzeskonform" — scrubbed inline + Log in notes. - _registry.py: AgentRegistry mit MC-Owner-Mapping (verhindert Doppel-Ownership). - _escalation.py: cascade(local → ovh). qwen2.5:7b default, OVH 120b als Stage-2 (deaktiviert wenn OVH_URL leer). - _rollup.py: deterministisches Dedup ähnlicher actions zu Recommendations mit related_finding_ids[]. - _evidence_vault.py: Pro-Run File-Vault für Playwright-Videos, Screenshots, CSV. SHA256 + manifest.json. DSR-tauglich (delete_run). Agenten: - ImpressumAgent v2 (impressum/agent.py + mcs.py) — konsolidiert v1-Pattern-Match + v2-LLM-MVP unter dem neuen Contract. 12 MCs. - CookiePolicyAgent v1 (cookie_policy/agent.py + mcs.py) — 12 MCs zu Cookie-Richtlinie-Vollständigkeit + KB-Layer für CMP-Vendor-Cross-Check. Tests: 25/25 grün (10 Impressum + 9 Vault + 6 Cookie-Policy). Roadmap: SSE-Test-Endpoint + Frontend-Tab → DSE/AGB-Agents → Cookie-Banner-Themen-Agent → Cross-Doc-Konsistenz-Agent. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
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"""Impressum-Specialist-Agent v2 — konsolidiert Pattern (v1) + LLM (v2-mvp).
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Public Entry-Point: ImpressumAgent (inherits BaseSpecialistAgent).
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"""
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from .agent import ImpressumAgent
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__all__ = ["ImpressumAgent"]
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"""Impressum-Agent v2 — konsolidierter BaseSpecialistAgent.
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Ablauf:
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1. Deterministische MCs durchlaufen → Findings + mc_coverage.
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2. Wenn unklare Felder (HIGH/MEDIUM missing) → LLM-Eskalation.
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3. LLM-Findings dedupen mit MC-Findings nach field_id.
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4. Rollup → Recommendations.
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5. Disclaimer-Lint → AgentOutput.
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Phase 1 (jetzt): qwen2.5:7b als Stage-1, OVH optional als Stage-2.
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"""
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from __future__ import annotations
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import logging
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from datetime import datetime, timezone
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from .._base import (
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AgentInput,
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AgentOutput,
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BaseSpecialistAgent,
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EscalationLog,
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EvidenceSource,
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Finding,
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McCoverage,
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Severity,
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SourceType,
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lint_output,
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)
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from .._escalation import cascade
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from .._rollup import rollup
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from .mcs import MC_IDS, MCS, detect_automotive, scope_matches
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logger = logging.getLogger(__name__)
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_SYSTEM_PROMPT = """Du bist ein deutscher Datenschutz-Anwalt mit Fokus
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§ 5 TMG / DDG (Anbieterkennzeichnung). Aufgabe: Impressum prüfen und
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LÜCKEN aufzählen, die einer regex-basierten Vorprüfung entgangen sind.
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WICHTIG:
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- KEINE Bewertung "rechtssicher" / "garantiert" / "konform".
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- Wenn unsicher: leeres Array zurückgeben statt zu halluzinieren.
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- Wörtliches Zitat als evidence bei jeder Lücke.
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Antworte NUR mit JSON, Schema:
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{"findings": [
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{"field_id": "...", "severity": "HIGH|MEDIUM|LOW",
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"title": "...", "evidence": "wörtliches Zitat",
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"action": "konkrete Empfehlung"}
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]}
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"""
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class ImpressumAgent(BaseSpecialistAgent):
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agent_id = "impressum"
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agent_version = "2.0"
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doc_type = "impressum"
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owned_mc_ids = MC_IDS
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async def evaluate(self, agent_input: AgentInput) -> AgentOutput:
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start = datetime.now(timezone.utc)
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text = (agent_input.text or "").strip()
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scope = set(agent_input.business_scope or [])
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# Auto-detect KFZ
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is_automotive = detect_automotive(text)
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if is_automotive:
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scope.add("automotive")
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mc_findings: list[Finding] = []
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coverage: list[McCoverage] = []
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if len(text) < 50:
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# Doc zu kurz → alle als skipped
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for mc in MCS:
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coverage.append(McCoverage(
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mc_id=mc.mc_id, status="skipped",
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reason="doc too short or empty",
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))
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return self._finalize(
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start, mc_findings, [], coverage, confidence=0.0,
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notes="Impressum-Text zu kurz oder leer.",
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)
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for mc in MCS:
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if not scope_matches(mc, scope, is_automotive):
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coverage.append(McCoverage(
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mc_id=mc.mc_id, status="na",
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reason=f"scope mismatch (needs {mc.requires_scope})",
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))
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continue
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found = any(p.search(text) for p in mc.patterns)
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if found:
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coverage.append(McCoverage(
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mc_id=mc.mc_id, status="ok",
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))
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continue
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# Missing → Finding
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sev = self._sev(mc.severity_if_missing)
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action = self._build_action(mc, is_automotive)
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mc_findings.append(Finding(
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check_id=f"IMPRESSUM-AGENT-{mc.field_id.upper()}",
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agent=self.agent_id,
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agent_version=self.agent_version,
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field_id=mc.field_id,
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severity=sev,
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severity_reason="missing",
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title=f"Pflichtangabe '{mc.label}' fehlt im Impressum",
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norm=mc.norm,
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evidence="",
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action=action,
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confidence=0.95,
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sources=[EvidenceSource(
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source_type=SourceType.MC,
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source_id=mc.mc_id,
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detail=f"regex check {len(mc.patterns)} pattern(s) negative",
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)],
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))
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coverage.append(McCoverage(
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mc_id=mc.mc_id,
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status=sev.value.lower(),
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reason="missing",
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))
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# Eskalation: für die identifizierten Lücken kann ein LLM
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# zusätzliche Tiefen-Findings liefern (z.B. "Geschäftsführer
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# genannt, aber ohne Nachname"). Confidence der MC-Findings
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# ist hoch — eskalieren wir wegen "weitere subtile Lücken
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# finden", nicht weil wir unsicher sind.
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esc_findings, esc_logs = await self._maybe_escalate(text, scope)
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# Dedup per field_id (MC hat Priorität)
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seen_fields = {f.field_id for f in mc_findings if f.field_id}
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for f in esc_findings:
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if f.field_id and f.field_id in seen_fields:
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continue
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mc_findings.append(f)
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# Confidence: harmonisches Mittel über alle Finding-Confidences
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if mc_findings:
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confs = [f.confidence for f in mc_findings if f.confidence]
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overall = sum(confs) / len(confs) if confs else 0.8
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else:
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overall = 0.95 # nichts gefunden → alle MCs ok
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return self._finalize(
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start, mc_findings, esc_logs, coverage, confidence=overall,
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)
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async def _maybe_escalate(
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self, text: str, scope: set[str],
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) -> tuple[list[Finding], list[EscalationLog]]:
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"""LLM-Stage. Aktivierbar via Agent-Settings (default an)."""
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# Hard cap auf Text-Größe für den LLM-Pass
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user_prompt = (
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f"BUSINESS-SCOPE: {', '.join(sorted(scope))}\n\n"
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f"IMPRESSUM-TEXT:\n{text[:4000]}\n\n"
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"Liste subtile Lücken nach § 5 TMG. Nur JSON."
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)
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res, logs = await cascade(_SYSTEM_PROMPT, user_prompt)
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if res is None or not isinstance(res.parsed, (dict, list)):
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return [], logs
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raw = (res.parsed.get("findings")
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if isinstance(res.parsed, dict) else res.parsed)
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if not isinstance(raw, list):
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return [], logs
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out: list[Finding] = []
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for item in raw:
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if not isinstance(item, dict):
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continue
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fid = str(item.get("field_id") or "unknown")[:40]
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sev_raw = str(item.get("severity") or "MEDIUM").upper()
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sev = self._sev(sev_raw)
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out.append(Finding(
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check_id=f"IMPRESSUM-AGENT-LLM-{fid.upper()}",
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agent=self.agent_id,
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agent_version=self.agent_version,
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field_id=fid,
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severity=sev,
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severity_reason="llm_detected",
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title=str(item.get("title") or "")[:200],
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norm="§ 5 TMG / DDG (LLM-Analyse)",
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evidence=str(item.get("evidence") or "")[:300],
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action=str(item.get("action") or "")[:400],
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confidence=0.7,
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sources=[EvidenceSource(
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source_type=res.stage,
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source_id=res.model,
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detail=f"prompt_chars={len(user_prompt)}",
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confidence=0.7,
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)],
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))
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return out, logs
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def _finalize(
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self,
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start: datetime,
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findings: list[Finding],
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esc_logs: list[EscalationLog],
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coverage: list[McCoverage],
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confidence: float,
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notes: str = "",
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) -> AgentOutput:
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end = datetime.now(timezone.utc)
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recs = rollup(findings)
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out = AgentOutput(
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agent=self.agent_id,
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agent_version=self.agent_version,
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started_at=start,
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finished_at=end,
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duration_ms=int((end - start).total_seconds() * 1000),
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findings=findings,
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recommendations=recs,
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mc_coverage=coverage,
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escalation_log=esc_logs,
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confidence=confidence,
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notes=notes,
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mc_total=len(coverage),
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mc_ok=sum(1 for c in coverage if c.status == "ok"),
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mc_na=sum(1 for c in coverage if c.status == "na"),
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mc_high=sum(1 for c in coverage if c.status == "high"),
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mc_medium=sum(1 for c in coverage if c.status == "medium"),
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mc_low=sum(1 for c in coverage if c.status == "low"),
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)
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return lint_output(out)
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@staticmethod
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def _sev(value: str) -> Severity:
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v = (value or "").upper()
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if v == "HIGH":
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return Severity.HIGH
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if v == "MEDIUM":
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return Severity.MEDIUM
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if v == "LOW":
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return Severity.LOW
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return Severity.INFO
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@staticmethod
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def _build_action(mc, is_automotive: bool) -> str:
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if mc.field_id == "aufsichtsbehoerde" and is_automotive:
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return (
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"Aufsichtsbehörde im Impressum benennen. Für "
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"KFZ-Hersteller/-Vertrieb typisch: Kraftfahrt-"
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"Bundesamt (KBA), Fördestraße 16, 24944 Flensburg, "
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"www.kba.de. Bei Ladestrom-Vertrieb zusätzlich "
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"Bundesnetzagentur (BNetzA)."
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)
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return (
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f"{mc.label} im Impressum ergänzen "
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f"(Pflichtangabe nach {mc.norm})."
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)
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@@ -0,0 +1,234 @@
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"""Machine-Check-Definitionen für den Impressum-Agent.
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Eine MC = ein abgegrenzter, deterministischer Check über das
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Impressum-Dokument. Owner = impressum-agent.
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Quelle: § 5 TMG / DDG + § 18 MStV + § 36 VSBG + Art. 14 EU-VO 524/2013.
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"""
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from __future__ import annotations
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import re
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from dataclasses import dataclass, field
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from typing import Pattern
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@dataclass(frozen=True)
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class MC:
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"""Eine Machine-Check-Definition."""
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mc_id: str # IMP-MC-001 ...
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field_id: str # name_anbieter, handelsregister, ...
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label: str
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norm: str
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patterns: tuple[Pattern[str], ...] = field(default_factory=tuple)
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severity_if_missing: str = "MEDIUM" # HIGH | MEDIUM | LOW | INFO
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requires_scope: tuple[str, ...] = field(default_factory=tuple)
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# Wenn True: bei Scope-Mismatch nicht-applicable melden, sonst skip
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explicit_na: bool = True
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MCS: tuple[MC, ...] = (
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MC(
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mc_id="IMP-MC-001",
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field_id="name_anbieter",
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label="Name + Anschrift des Anbieters",
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norm="§ 5 Abs. 1 Nr. 1 TMG",
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severity_if_missing="HIGH",
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patterns=(
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re.compile(
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r"\b(?:Anbieter|Diensteanbieter|"
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r"Verantwortlich(?:er Anbieter)?)\s*[:.\s]",
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re.IGNORECASE,
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),
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# Label-free fallback: Firma (Rechtsform) + Adresse
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re.compile(
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r"\b[A-ZÄÖÜ][\w\-\& ]{1,80}?\s+"
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r"(?:GmbH|AG|UG|KG|SE|GbR|OHG|Limited|Ltd|LLC)\s*"
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r"[\s\S]{0,400}?"
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r"\b\d{5}\s+[A-ZÄÖÜ]",
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re.IGNORECASE,
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),
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),
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),
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MC(
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mc_id="IMP-MC-002",
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field_id="kontakt_email",
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label="Email-Adresse",
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norm="§ 5 Abs. 1 Nr. 2 TMG",
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severity_if_missing="HIGH",
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patterns=(re.compile(r"\b[\w.+-]+@[\w-]+\.[a-z]{2,}\b",
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re.IGNORECASE),),
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),
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MC(
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mc_id="IMP-MC-003",
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field_id="kontakt_telefon",
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label="Telefon",
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norm="§ 5 Abs. 1 Nr. 2 TMG",
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severity_if_missing="MEDIUM",
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patterns=(re.compile(
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r"(?:Tel(?:efon)?|Phone)\.?\s*[:.\s]\s*[\+\d][\d\s/\-()]{5,}",
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re.IGNORECASE,
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),),
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),
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MC(
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mc_id="IMP-MC-004",
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field_id="handelsregister",
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label="Handelsregister-Eintrag",
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norm="§ 5 Abs. 1 Nr. 4 TMG",
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severity_if_missing="HIGH",
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patterns=(
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re.compile(r"\bHR[BA]\s+\d", re.IGNORECASE),
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re.compile(r"Handelsregister", re.IGNORECASE),
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),
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),
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MC(
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mc_id="IMP-MC-005",
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field_id="ust_id",
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label="USt-IdNr",
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norm="§ 5 Abs. 1 Nr. 6 TMG",
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severity_if_missing="MEDIUM",
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patterns=(
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re.compile(
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r"\b(?:USt-?Id(?:Nr)?\.?|VAT(?:-?Id)?)\s*[:.\s]",
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re.IGNORECASE,
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),
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re.compile(r"\bDE\d{9}\b"),
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),
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),
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MC(
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mc_id="IMP-MC-006",
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field_id="vertretungsberechtigte",
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label="Vertretungsberechtigte Person",
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norm="§ 5 Abs. 1 Nr. 1 TMG (juristische Personen)",
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severity_if_missing="HIGH",
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patterns=(
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re.compile(
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r"(?:Gesch(?:ae|ä)ftsf(?:ue|ü)hrer|"
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r"Vertretungsberechtigt|vertreten\s+durch)"
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r"\s*[:.\s]",
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re.IGNORECASE,
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),
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re.compile(r"\bManagement\s*[:.\s]\s*[A-ZÄÖÜ]",
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re.IGNORECASE),
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re.compile(r"\bDirector(?:s|en)?\s*[:.\s]\s*[A-ZÄÖÜ]",
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re.IGNORECASE),
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),
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),
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MC(
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mc_id="IMP-MC-007",
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field_id="vertretungsberechtigte_label_korrekt",
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label="Deutsches Label 'Geschäftsführer' statt 'Management'",
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norm="§ 5 Abs. 1 Nr. 1 TMG (Deutsch-Pflicht, gerichtsfest)",
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severity_if_missing="MEDIUM",
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patterns=(re.compile(
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r"(?:Gesch(?:ae|ä)ftsf(?:ue|ü)hrer|"
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r"Vorstand|"
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r"Vertretungsberechtigt|vertreten\s+durch)"
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r"\s*[:.\s]",
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re.IGNORECASE,
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),),
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),
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MC(
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mc_id="IMP-MC-008",
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field_id="aufsichtsbehoerde",
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label="Aufsichtsbehörde (regulierte Branchen)",
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norm="§ 5 Abs. 1 Nr. 3 TMG (Branchen-bedingt)",
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severity_if_missing="LOW",
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requires_scope=("regulated_profession", "financial_services",
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"insurance", "automotive"),
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patterns=(
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re.compile(r"Aufsichtsbeh(?:ö|oe)rde\s*[:.\s]",
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re.IGNORECASE),
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re.compile(
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r"\bBAFin\b|\bBNetzA\b|\bLKA\b|\bKBA\b|"
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r"Kraftfahrt-?Bundesamt|Bundesnetzagentur|"
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r"Bundesanstalt\s+f(?:ü|ue)r",
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re.IGNORECASE,
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),
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),
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),
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MC(
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mc_id="IMP-MC-009",
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field_id="verantwortlicher_redaktion",
|
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label="Verantwortlicher § 18 MStV (journalistisch-redaktionell)",
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norm="§ 18 MStV (bei Blog/News/Magazin/Newsroom Pflicht)",
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severity_if_missing="MEDIUM",
|
||||
requires_scope=("editorial",),
|
||||
patterns=(re.compile(
|
||||
r"(?:Verantwortlich(?:er|e)?\s+(?:f(?:ue|ü)r|i\.S\.d\.|"
|
||||
r"nach|gem(?:ae|ä)ß)\s+§\s*18|"
|
||||
r"V\.i\.S\.d\.\s*§?\s*18|"
|
||||
r"redaktionell\s+Verantwortlich)",
|
||||
re.IGNORECASE,
|
||||
),),
|
||||
),
|
||||
MC(
|
||||
mc_id="IMP-MC-010",
|
||||
field_id="verbraucher_streitbeilegung",
|
||||
label="Verbraucher-Streitbeilegung-Hinweis",
|
||||
norm="§ 36 VSBG (B2C-Anbieter Pflicht)",
|
||||
severity_if_missing="MEDIUM",
|
||||
requires_scope=("ecommerce", "b2c"),
|
||||
patterns=(re.compile(
|
||||
r"(?:Verbraucherschlichtungs|VSBG|"
|
||||
r"Streitbeilegung|"
|
||||
r"Schlichtungsstelle|"
|
||||
r"alternative\s+Streit(?:beilegung|schlichtung))",
|
||||
re.IGNORECASE,
|
||||
),),
|
||||
),
|
||||
MC(
|
||||
mc_id="IMP-MC-011",
|
||||
field_id="berufsangaben",
|
||||
label="Berufsbezeichnung + Berufsrechtliche Angaben",
|
||||
norm="§ 5 Abs. 1 Nr. 5 TMG (Kammerberufe)",
|
||||
severity_if_missing="LOW",
|
||||
requires_scope=("regulated_profession",),
|
||||
patterns=(re.compile(
|
||||
r"Berufsbezeichnung|Berufsordnung|Kammer", re.IGNORECASE,
|
||||
),),
|
||||
),
|
||||
MC(
|
||||
mc_id="IMP-MC-012",
|
||||
field_id="odr_link",
|
||||
label="OS-Link auf EU-Plattform",
|
||||
norm="Art. 14 EU-VO 524/2013 (B2C-Onlineshops)",
|
||||
severity_if_missing="MEDIUM",
|
||||
requires_scope=("ecommerce",),
|
||||
patterns=(re.compile(r"ec\.europa\.eu/consumers/odr",
|
||||
re.IGNORECASE),),
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
# Public list of all MC-IDs for the Registry
|
||||
MC_IDS: tuple[str, ...] = tuple(m.mc_id for m in MCS)
|
||||
|
||||
|
||||
def scope_matches(mc: MC, scope: set[str], is_automotive: bool) -> bool:
|
||||
"""Entscheidet ob die MC auf den Business-Scope anwendbar ist."""
|
||||
if not mc.requires_scope:
|
||||
return True
|
||||
if mc.field_id == "aufsichtsbehoerde" and is_automotive:
|
||||
return True
|
||||
return any(s in scope for s in mc.requires_scope)
|
||||
|
||||
|
||||
def detect_automotive(text: str) -> bool:
|
||||
"""KFZ-Hersteller/-Vertrieb → triggert KBA-Hint."""
|
||||
if re.search(
|
||||
r"\b(?:KFZ|Fahrzeug(?:e|herstellung|verkauf)?|Automobil|"
|
||||
r"E-Auto|Elektroauto|Auto-?Konfigurator|"
|
||||
r"Elektrofahrzeug|Hybrid-?Fahrzeug)\b",
|
||||
text, re.IGNORECASE,
|
||||
):
|
||||
return True
|
||||
return bool(re.search(
|
||||
r"\b(?:Tesla|BMW|Mercedes-?Benz|Audi|Volkswagen|Porsche|"
|
||||
r"Volvo|Stellantis|Skoda|Seat|Cupra|MINI|Smart|"
|
||||
r"Opel|Ford\s+Deutschland|Hyundai|Kia|Toyota|Mazda|"
|
||||
r"Nissan|Honda|Subaru|Lexus|Polestar|NIO|BYD|Rivian|"
|
||||
r"Lucid)\s+(?:Germany|Deutschland|Group|Holding|AG|"
|
||||
r"GmbH|S(?:E|\.A\.))\b",
|
||||
text, re.IGNORECASE,
|
||||
))
|
||||
Reference in New Issue
Block a user