After Automotive, pause on domains and ask the deeper question: not "which MCAPs occur most often?" (frequency deceives) but "which MCAPs CARRY the largest part of the system?". A deterministic MCAP Impact Score (no AI) aggregates over the EXISTING data only: Impact = distinct Sources + Target Types + Domains + Journeys + Regulatory + Business Leverage Critically anti-frequency-deception: a `likely_covered` cap is attributed to its source CERT (one source), not to every target regulation — otherwise generic management caps win on raw frequency. With that fix the Core surfaces the true cross-cutting nodes: secure_signed_update_distribution (18), technical_vulnerability_management (17), access_control, incident_management, sbom_creation, product_cyber_risk_assessment — exactly the bridges the user predicted; the high-frequency single- domain environmental management caps correctly drop out. Four reports, pure aggregation (no runtime, no new architecture): Core (highest impact), Emerging (>=2 domains), Isolated (1 source/journey — specialised or convergence-not-yet-seen), Suspicious (too coarse: generic verbs; too fine: hyper-specific isolated names) — an abstraction-level review tool for domain experts. 11/62 caps already reach impact >=8; the method is ready to reveal whether a 30-50 MCAP core forms as Medical/Payment arrive. Non-runtime -> no deploy. 5 tests pass, check-loc 0.
backend-compliance
Python/FastAPI service implementing the DSGVO compliance API: DSR, DSFA, consent, controls, risks, evidence, audit, vendor management, ISMS, change requests, document generation.
Port: 8002 (container: bp-compliance-backend)
Stack: Python 3.12, FastAPI, SQLAlchemy 2.x, Alembic, Keycloak auth.
Architecture
compliance/
├── api/ # Routers (thin, ≤30 LOC per handler)
├── services/ # Business logic
├── repositories/ # DB access
├── domain/ # Value objects, domain errors
├── schemas/ # Pydantic models, split per domain
└── db/models/ # SQLAlchemy ORM, one module per aggregate
The service follows this layered target structure but not all files are fully refactored yet. Phase 1 backlog is tracked in .claude/rules/loc-exceptions.txt (27 backend-compliance files currently excepted).
See ../AGENTS.python.md for the full convention and ../.claude/rules/architecture.md for the non-negotiable rules.
Run locally
cd backend-compliance
pip install -r requirements.txt
export COMPLIANCE_DATABASE_URL=... # Postgres (Hetzner or local)
uvicorn main:app --reload --port 8002
Tests
pytest compliance/tests/ -v
pytest --cov=compliance --cov-report=term-missing
Layout: tests/unit/, tests/integration/, tests/contracts/. Contract tests diff /openapi.json against tests/contracts/openapi.baseline.json.
Public API surface
404+ endpoints across /api/v1/*. Grouped by domain: ai, audit, consent, dsfa, dsr, gdpr, vendor, evidence, change-requests, generation, projects, company-profile, isms. Every path is a contract — see the "Public endpoints" rule in the root CLAUDE.md.
Environment
| Var | Purpose |
|---|---|
COMPLIANCE_DATABASE_URL |
Postgres DSN, sslmode=require |
KEYCLOAK_* |
Auth verification |
QDRANT_URL, QDRANT_API_KEY |
Vector search |
CORE_VALKEY_URL |
Session cache |
Don't touch
Database schema, __tablename__, column names, existing migrations under migrations/. See root CLAUDE.md rule 3.