fix(freigabe): Vorbereitung-Module release prep — Python 3.9 fix, Scope Engine tests, MkDocs
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- fix: company_profile_routes.py — dict|None → Optional[dict] for Python 3.9 compat (9/9 tests grün)
- test: 40 Vitest-Tests für ComplianceScopeEngine (calculateScores, determineLevel,
  evaluateHardTriggers, evaluate integration, buildDocumentScope, evaluateRiskFlags)
- docs: vorbereitung-module.md — Profil, Scope, UCCA vollständig dokumentiert
- docs: mkdocs.yml — Nav-Eintrag "Vorbereitung-Module (Paket 1)" vor Analyse-Module

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-03-05 10:57:17 +01:00
parent 6ad7d62369
commit 0503e72a80
4 changed files with 642 additions and 1 deletions

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@@ -0,0 +1,372 @@
import { describe, it, expect } from 'vitest'
import { complianceScopeEngine } from '../compliance-scope-engine'
// Helper: create an answer object (engine reads answerValue + questionId)
function ans(questionId: string, answerValue: unknown) {
return { questionId, answerValue } as any
}
// Helper: create a minimal triggered-trigger (engine shape, not types shape)
function trigger(ruleId: string, minimumLevel: string, opts: Record<string, unknown> = {}) {
return { ruleId, minimumLevel, mandatoryDocuments: [], requiresDSFA: false, category: 'test', ...opts } as any
}
// ============================================================================
// calculateScores
// ============================================================================
describe('calculateScores', () => {
it('returns zero composite for empty answers', () => {
const scores = complianceScopeEngine.calculateScores([])
expect(scores.composite).toBe(0)
expect(scores.risk).toBe(0)
expect(scores.complexity).toBe(0)
expect(scores.assurance).toBe(0)
})
it('all-false boolean answers → zero composite', () => {
const scores = complianceScopeEngine.calculateScores([
ans('data_art9', false),
ans('data_minors', false),
ans('proc_ai_usage', false),
])
expect(scores.composite).toBe(0)
})
it('boolean true answer increases risk score', () => {
const scoresFalse = complianceScopeEngine.calculateScores([ans('data_art9', false)])
const scoresTrue = complianceScopeEngine.calculateScores([ans('data_art9', true)])
expect(scoresTrue.risk).toBeGreaterThan(scoresFalse.risk)
})
it('composite is weighted sum: risk×0.4 + complexity×0.3 + assurance×0.3', () => {
const scores = complianceScopeEngine.calculateScores([ans('data_art9', true)])
const expected = Math.round((scores.risk * 0.4 + scores.complexity * 0.3 + scores.assurance * 0.3) * 10) / 10
expect(scores.composite).toBe(expected)
})
it('numeric answer uses logarithmic normalization — higher value → higher score', () => {
const scoresLow = complianceScopeEngine.calculateScores([ans('data_volume', 10)])
const scoresHigh = complianceScopeEngine.calculateScores([ans('data_volume', 999)])
expect(scoresHigh.composite).toBeGreaterThan(scoresLow.composite)
})
it('array answer score proportional to count (max 1.0 at 5+)', () => {
const scores1 = complianceScopeEngine.calculateScores([ans('data_art9', ['gesundheit'])])
const scores5 = complianceScopeEngine.calculateScores([
ans('data_art9', ['gesundheit', 'biometrie', 'genetik', 'politisch', 'religion']),
])
expect(scores5.composite).toBeGreaterThan(scores1.composite)
})
it('empty array answer → zero contribution', () => {
const scoresEmpty = complianceScopeEngine.calculateScores([ans('data_art9', [])])
const scoresNone = complianceScopeEngine.calculateScores([])
expect(scoresEmpty.composite).toBe(scoresNone.composite)
})
})
// ============================================================================
// determineLevel
// ============================================================================
describe('determineLevel', () => {
it('composite ≤25 → L1', () => {
const level = complianceScopeEngine.determineLevel({ composite: 20 } as any, [])
expect(level).toBe('L1')
})
it('composite exactly 25 → L1', () => {
const level = complianceScopeEngine.determineLevel({ composite: 25 } as any, [])
expect(level).toBe('L1')
})
it('composite 2650 → L2', () => {
const level = complianceScopeEngine.determineLevel({ composite: 40 } as any, [])
expect(level).toBe('L2')
})
it('composite exactly 50 → L2', () => {
const level = complianceScopeEngine.determineLevel({ composite: 50 } as any, [])
expect(level).toBe('L2')
})
it('composite 5175 → L3', () => {
const level = complianceScopeEngine.determineLevel({ composite: 60 } as any, [])
expect(level).toBe('L3')
})
it('composite >75 → L4', () => {
const level = complianceScopeEngine.determineLevel({ composite: 80 } as any, [])
expect(level).toBe('L4')
})
it('hard trigger with minimumLevel L3 overrides score-based L1', () => {
const t = trigger('HT-A01', 'L3')
const level = complianceScopeEngine.determineLevel({ composite: 10 } as any, [t])
expect(level).toBe('L3')
})
it('hard trigger with minimumLevel L4 overrides score-based L2', () => {
const t = trigger('HT-F01', 'L4')
const level = complianceScopeEngine.determineLevel({ composite: 40 } as any, [t])
expect(level).toBe('L4')
})
it('level = max(score-level, trigger-level) — score wins when higher', () => {
const t = trigger('HT-B01', 'L2')
// score gives L3, trigger gives L2 → max = L3
const level = complianceScopeEngine.determineLevel({ composite: 60 } as any, [t])
expect(level).toBe('L3')
})
it('no triggers with zero composite → L1', () => {
const level = complianceScopeEngine.determineLevel({ composite: 0 } as any, [])
expect(level).toBe('L1')
})
})
// ============================================================================
// evaluateHardTriggers
// ============================================================================
describe('evaluateHardTriggers', () => {
it('empty answers → no triggers', () => {
const triggers = complianceScopeEngine.evaluateHardTriggers([])
expect(triggers).toHaveLength(0)
})
it('art9 health data answer triggers category art9 with minimumLevel L3', () => {
const triggers = complianceScopeEngine.evaluateHardTriggers([
ans('data_art9', ['gesundheit']),
])
const art9 = triggers.find((t: any) => t.category === 'art9')
expect(art9).toBeDefined()
expect((art9 as any).minimumLevel).toBe('L3')
})
it('minors answer sets requiresDSFA = true', () => {
const triggers = complianceScopeEngine.evaluateHardTriggers([
ans('data_minors', true),
])
const minorsTrigger = triggers.find((t: any) => t.category === 'vulnerable')
expect(minorsTrigger).toBeDefined()
expect((minorsTrigger as any).requiresDSFA).toBe(true)
})
it('AI scoring usage answer triggers minimumLevel L2 (adm category)', () => {
const triggers = complianceScopeEngine.evaluateHardTriggers([
ans('proc_ai_usage', ['scoring']),
])
const aiTrigger = triggers.find((t: any) => t.category === 'adm')
expect(aiTrigger).toBeDefined()
expect(['L2', 'L3', 'L4']).toContain((aiTrigger as any).minimumLevel)
})
it('multiple triggers all returned when multiple questions answered', () => {
const triggers = complianceScopeEngine.evaluateHardTriggers([
ans('data_art9', ['gesundheit']),
ans('data_minors', true),
])
expect(triggers.length).toBeGreaterThanOrEqual(2)
})
it('false answer for boolean trigger does not fire it', () => {
const triggersBefore = complianceScopeEngine.evaluateHardTriggers([])
const triggersWithFalse = complianceScopeEngine.evaluateHardTriggers([
ans('data_minors', false),
])
expect(triggersWithFalse.length).toBe(triggersBefore.length)
})
})
// ============================================================================
// evaluate — integration
// ============================================================================
describe('evaluate — integration', () => {
it('empty answers → L1 ScopeDecision with all required fields', () => {
const decision = complianceScopeEngine.evaluate([])
expect(decision.scores).toBeDefined()
expect(decision.triggeredHardTriggers).toBeDefined()
expect(decision.requiredDocuments).toBeDefined()
expect(decision.riskFlags).toBeDefined()
expect(decision.gaps).toBeDefined()
expect(decision.nextActions).toBeDefined()
expect(decision.reasoning).toBeDefined()
expect(decision.determinedLevel).toBe('L1')
expect(decision.evaluatedAt).toBeDefined()
})
it('art9 + minors answers → determinedLevel L3 or L4', () => {
const decision = complianceScopeEngine.evaluate([
ans('data_art9', ['gesundheit', 'biometrie']),
ans('data_minors', true),
])
expect(['L3', 'L4']).toContain(decision.determinedLevel)
})
it('triggeredHardTriggers populated on evaluate with art9 answer', () => {
const decision = complianceScopeEngine.evaluate([
ans('data_art9', ['gesundheit']),
])
expect(decision.triggeredHardTriggers.length).toBeGreaterThan(0)
})
it('composite score non-negative', () => {
const decision = complianceScopeEngine.evaluate([ans('org_employee_count', '50-249')])
expect((decision.scores as any).composite).toBeGreaterThanOrEqual(0)
})
it('evaluate returns array types for collections', () => {
const decision = complianceScopeEngine.evaluate([])
expect(Array.isArray(decision.triggeredHardTriggers)).toBe(true)
expect(Array.isArray(decision.requiredDocuments)).toBe(true)
expect(Array.isArray(decision.riskFlags)).toBe(true)
expect(Array.isArray(decision.gaps)).toBe(true)
expect(Array.isArray(decision.nextActions)).toBe(true)
})
})
// ============================================================================
// buildDocumentScope
// ============================================================================
describe('buildDocumentScope', () => {
it('returns an array', () => {
const docs = complianceScopeEngine.buildDocumentScope('L1', [], [])
expect(Array.isArray(docs)).toBe(true)
})
it('each returned document has documentType, label, estimatedEffort', () => {
// Use a trigger with uppercase docType to test engine behaviour
const t = trigger('HT-A01', 'L3', {
category: 'art9',
mandatoryDocuments: ['VVT'],
})
const docs = complianceScopeEngine.buildDocumentScope('L3', [t], [])
docs.forEach((doc: any) => {
expect(doc.documentType).toBeDefined()
expect(doc.label).toBeDefined()
expect(typeof doc.estimatedEffort).toBe('number')
expect(doc.estimatedEffort).toBeGreaterThan(0)
})
})
it('mandatory documents have high priority', () => {
const t = trigger('HT-A01', 'L3', {
category: 'art9',
mandatoryDocuments: ['VVT'],
})
const docs = complianceScopeEngine.buildDocumentScope('L3', [t], [])
const mandatoryDocs = docs.filter((d: any) => d.requirement === 'mandatory')
mandatoryDocs.forEach((doc: any) => {
expect(doc.priority).toBe('high')
})
})
it('documents sorted: mandatory first', () => {
const decision = complianceScopeEngine.evaluate([
ans('data_art9', ['gesundheit']),
])
const docs = decision.requiredDocuments
if (docs.length > 1) {
// mandatory docs should appear before recommended ones
let seenNonMandatory = false
for (const doc of docs) {
if ((doc as any).requirement !== 'mandatory') seenNonMandatory = true
if (seenNonMandatory) {
expect((doc as any).requirement).not.toBe('mandatory')
}
}
}
})
it('sdkStepUrl present for known document types when available', () => {
const decision = complianceScopeEngine.evaluate([
ans('data_art9', ['gesundheit']),
])
// sdkStepUrl is optional — just verify it's a string when present
decision.requiredDocuments.forEach((doc: any) => {
if (doc.sdkStepUrl !== undefined) {
expect(typeof doc.sdkStepUrl).toBe('string')
}
})
})
})
// ============================================================================
// evaluateRiskFlags
// ============================================================================
describe('evaluateRiskFlags', () => {
it('no answers → empty flags array', () => {
const flags = complianceScopeEngine.evaluateRiskFlags([], 'L1')
expect(Array.isArray(flags)).toBe(true)
})
it('no encryption transit at L2+ → high risk flag (technical)', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[ans('tech_encryption_transit', false)],
'L2',
)
const encFlag = flags.find((f: any) => f.category === 'technical')
expect(encFlag).toBeDefined()
expect((encFlag as any).severity).toBe('high')
})
it('no encryption rest at L2+ → high risk flag (technical)', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[ans('tech_encryption_rest', false)],
'L2',
)
const encFlag = flags.find((f: any) => f.category === 'technical')
expect(encFlag).toBeDefined()
expect((encFlag as any).severity).toBe('high')
})
it('encryption flags not raised at L1', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[ans('tech_encryption_transit', false)],
'L1',
)
const encFlag = flags.find((f: any) => f.message?.includes('Verschlüsselung'))
expect(encFlag).toBeUndefined()
})
it('third country transfer without guarantees → legal flag', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[
ans('tech_third_country', true),
ans('tech_hosting_location', 'drittland'),
],
'L1',
)
const legalFlag = flags.find((f: any) => f.category === 'legal')
expect(legalFlag).toBeDefined()
})
it('≥250 employees without DPO → organizational flag', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[
ans('org_has_dpo', false),
ans('org_employee_count', '250-999'),
],
'L2',
)
const orgFlag = flags.find((f: any) => f.category === 'organizational')
expect(orgFlag).toBeDefined()
})
it('DPO present with 250+ employees → no DPO flag', () => {
const flags = complianceScopeEngine.evaluateRiskFlags(
[
ans('org_has_dpo', true),
ans('org_employee_count', '250-999'),
],
'L2',
)
const orgFlag = flags.find((f: any) => f.category === 'organizational')
expect(orgFlag).toBeUndefined()
})
})

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@@ -139,7 +139,7 @@ def row_to_response(row) -> CompanyProfileResponse:
)
def log_audit(db, tenant_id: str, action: str, changed_fields: dict | None, changed_by: str | None):
def log_audit(db, tenant_id: str, action: str, changed_fields: Optional[dict], changed_by: Optional[str]):
"""Write an audit log entry."""
try:
db.execute(

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# Vorbereitung-Module (Paket 1)
Die drei Vorbereitung-Module bilden die Grundlage des SDK-Workflows. Sie erfassen das Unternehmensprofil, bestimmen den passenden Compliance-Umfang und bewerten konkrete KI/Daten-Anwendungsfälle.
| Modul | Code | Route | Backend |
|-------|------|-------|---------|
| **Company Profile** | CP-PROF | `/sdk/company-profile` | FastAPI `backend-compliance` |
| **Compliance Scope** | CP-SCOPE | `/sdk/compliance-scope` | FastAPI `backend-compliance` |
| **Use-Case Assessment** | CP-UC | `/sdk/use-cases` | Go `ai-compliance-sdk` |
---
## Profil — company-profile (CP-PROF)
### Übersicht
6-Schritt-Wizard zur Erfassung des vollständigen Unternehmensprofils. Speichert hybrid in `localStorage` (Draft) und der DB (Endstand).
### API-Endpunkte
| Methode | Pfad | Beschreibung |
|---------|------|--------------|
| `GET` | `/v1/company-profile` | Profil für Tenant laden |
| `POST` | `/v1/company-profile` | Profil erstellen oder aktualisieren (Upsert) |
| `PATCH` | `/v1/company-profile` | Einzelne Felder aktualisieren |
| `DELETE` | `/v1/company-profile` | Profil löschen (Art. 17 DSGVO) |
| `GET` | `/v1/company-profile/audit` | Audit-Log der Profiländerungen |
### Datenbankstruktur
**Tabelle:** `compliance_company_profiles` (Migration 005)
28 Felder, u.a.:
```sql
id UUID PRIMARY KEY
tenant_id TEXT UNIQUE NOT NULL
company_name TEXT
legal_form TEXT -- GmbH, AG, GbR, ...
industry TEXT -- tech, finance, healthcare, public, retail, education
company_size TEXT -- micro, small, medium, large
employee_count TEXT -- 1-9, 10-49, 50-249, 250-999, 1000+
uses_ai BOOLEAN
ai_use_cases JSONB
dpo_name TEXT
machine_builder JSONB -- IACE-Profil für Maschinenbauer
is_complete BOOLEAN
completed_at TIMESTAMPTZ
```
**Audit-Tabelle:** `compliance_company_profile_audit`
```sql
id UUID PRIMARY KEY
tenant_id TEXT
action TEXT -- create | update | delete
changed_fields JSONB
changed_by TEXT
created_at TIMESTAMPTZ
```
### Request-Modell (CompanyProfileRequest)
```json
{
"company_name": "Beispiel GmbH",
"legal_form": "GmbH",
"industry": "tech",
"founded_year": 2018,
"business_model": "B2B",
"company_size": "small",
"employee_count": "10-49",
"annual_revenue": "2-10 Mio",
"headquarters_country": "DE",
"uses_ai": true,
"ai_use_cases": ["Chatbot", "Dokumentenklassifikation"],
"is_complete": true
}
```
### Tests
**Datei:** `backend-compliance/tests/test_company_profile_routes.py`
9 Tests — alle grün:
- `test_get_profile_not_found` — 404 wenn kein Profil
- `test_create_profile` — POST legt Profil an
- `test_upsert_profile_update` — POST auf bestehendem Profil → UPDATE
- `test_delete_profile` — DELETE entfernt Profil
- `test_delete_profile_not_found` — 404 bei fehlendem Profil
- `test_get_audit_log_empty` — leeres Audit-Log
- `test_audit_log_after_create` — Audit-Eintrag nach CREATE
- `test_audit_log_after_delete` — Audit-Eintrag nach DELETE
- `test_complete_profile_workflow` — End-to-End Workflow
---
## Scope — compliance-scope (CP-SCOPE)
### Übersicht
4-Tab-Oberfläche zur Bestimmung des optimalen Compliance-Levels (L1L4):
| Tab | Inhalt |
|-----|--------|
| **Overview** | Aktueller Level, Score-Visualisierung, Dokumenten-Anforderungen |
| **Wizard** | 35 Fragen in 6 Blöcken (ca. 1015 min) |
| **Entscheidung** | Begründung, Hard Triggers, Gap-Analyse |
| **Export** | JSON/PDF-Export der Scope-Entscheidung |
### ComplianceScopeEngine
Die Engine (`lib/sdk/compliance-scope-engine.ts`) implementiert eine 8-Schritt-Pipeline:
```
1. calculateScores(answers) → ComplianceScores
2. evaluateHardTriggers(answers) → TriggeredHardTrigger[]
3. determineLevel(scores, triggers) → ComplianceDepthLevel
4. buildDocumentScope(level, ...) → RequiredDocument[]
5. evaluateRiskFlags(answers, level) → RiskFlag[]
6. calculateGaps(answers, level) → ScopeGap[]
7. buildNextActions(docs, gaps) → NextAction[]
8. buildReasoning(...) → ScopeReasoning[]
```
### Level-Modell
| Level | Composite-Score | Bezeichnung |
|-------|----------------|-------------|
| **L1** | ≤ 25 | Lean Startup — Minimalansatz |
| **L2** | 2650 | KMU Standard |
| **L3** | 5175 | Erweitert |
| **L4** | > 75 | Zertifizierungsbereit |
Finale Stufe = `max(score-basiertes Level, höchstes Hard-Trigger-Level)`
### Score-Gewichte
```
Composite = Risk × 0.4 + Complexity × 0.3 + Assurance × 0.3
```
Scores werden aus 35 gewichteten Fragen berechnet. Jede Frage hat individuelle Gewichte für `risk`, `complexity`, `assurance` (definiert in `QUESTION_SCORE_WEIGHTS`).
### Hard Trigger Kategorien (50 Regeln)
| Kategorie | Regeln | Beispiel-Trigger |
|-----------|--------|-----------------|
| `art9` | 9 | Gesundheits-, Biometrie-, Genetikdaten → mind. L3 |
| `vulnerable` | 3 | Minderjährige → L3/L4 + DSFA |
| `adm` | 6 | Autonome KI, Profiling, Scoring → L2/L3 |
| `surveillance` | 5 | Videoüberwachung, Mitarbeitermonitoring → L2/L3 |
| `third_country` | 5 | Drittland-Transfer → L2/L3 |
| `certification` | 5 | ISO 27001, SOC2, TISAX → L4 |
| `scale` | 5 | >1Mio Datensätze, >250 Mitarbeiter → L3 |
| `product` | 7 | Webshop, Datenmakler, B2C → L2/L3 |
| `process_maturity` | 5 | Fehlende Prozesse (DSAR, Löschung, Incident) |
| `iace_*` | 5+ | Maschinenbauer: AI Act, CRA, NIS2 |
### API-Endpunkte
| Methode | Pfad | Beschreibung |
|---------|------|--------------|
| `GET` | `/v1/compliance-scope` | Scope-Zustand laden (`sdk_states` JSONB) |
| `POST` | `/v1/compliance-scope` | Scope-Zustand speichern (JSONB UPSERT) |
Scope-Daten werden in `sdk_states.state->'compliance_scope'` als JSONB gespeichert.
### Tests
**Datei:** `backend-compliance/tests/test_compliance_scope_routes.py` — 27 Tests
**Datei:** `admin-compliance/lib/sdk/__tests__/compliance-scope-engine.test.ts` — 40 Vitest-Tests
Engine-Tests decken ab:
- `calculateScores`: Leer-Array, boolean/numeric/array Antworten, Composite-Gewichtung
- `determineLevel`: L1L4 Schwellenwerte, Hard-Trigger-Override, Level-Maximum
- `evaluateHardTriggers`: Art. 9, Minderjährige, KI-Scoring, mehrere Trigger
- `evaluate` (Integration): Vollständige ScopeDecision, Felder vorhanden, Level-Bestimmung
- `buildDocumentScope`: Array-Rückgabe, Dokumentstruktur, Sortierung
- `evaluateRiskFlags`: Verschlüsselung, Drittland, DPO-Pflicht
---
## Anwendung — use-case-assessment / UCCA (CP-UC)
### Übersicht
Bewertet konkrete Datenanwendungen hinsichtlich DSGVO- und AI-Act-Konformität. Gibt eine **Machbarkeitsentscheidung** (Feasibility) und detaillierte Befunde zurück.
| Ansicht | Inhalt |
|---------|--------|
| **Liste** | Alle Assessments mit Filter, Pagination, RiskScoreGauge |
| **Detail** | Vollständiger Befund-Report mit Kategorien, Controls |
| **Neu** | Wizard-Formular zur Assessment-Erstellung |
### Feasibility-Werte
| Wert | Bedeutung |
|------|-----------|
| `YES` | Umsetzung ohne Einschränkungen empfohlen |
| `CONDITIONAL` | Umsetzung nur mit spezifischen Maßnahmen |
| `NO` | Umsetzung nicht empfohlen (unakzeptables Risiko) |
### Risiko-Level
| Level | Score-Bereich |
|-------|--------------|
| `MINIMAL` | 020 |
| `LOW` | 2140 |
| `MEDIUM` | 4160 |
| `HIGH` | 6180 |
| `UNACCEPTABLE` | 81100 |
### Backend: ai-compliance-sdk (Go)
**Service:** `bp-compliance-ai-sdk` (Port 8090 intern, 8093 extern)
Relevante Module in `internal/ucca/`:
| Datei | Funktion |
|-------|---------|
| `policy_engine.go` | Zentrale Regelauswertung |
| `dsgvo_module.go` | DSGVO-spezifische Prüfungen (Art. 59, 22, 35) |
| `ai_act_module.go` | AI-Act Risikokategorisierung |
| `nis2_module.go` | NIS2-Anforderungen |
| `escalation.go` | Eskalationslogik bei Hochrisiko |
| `handlers.go` | HTTP Handler (Gin) |
**Datenbanktabellen:**
```sql
ucca_assessments -- Assessments (tenant_id, title, description, status, feasibility, risk_level)
ucca_findings -- Einzelbefunde pro Assessment
ucca_controls -- Empfohlene Maßnahmen
```
### Proxy
```
Frontend /api/sdk/v1/ucca/**
→ ai-compliance-sdk:8090/ucca/**
```
Proxy-Datei: `admin-compliance/app/api/sdk/v1/ucca/[[...path]]/route.ts`
### Tests
8 Go-Test-Dateien in `ai-compliance-sdk/internal/ucca/`:
```
handlers_test.go
policy_engine_test.go
dsgvo_module_test.go
ai_act_module_test.go
nis2_module_test.go
escalation_test.go
assessment_test.go
feasibility_test.go
```
Ausführen auf Mac Mini:
```bash
ssh macmini "/usr/local/bin/docker exec bp-compliance-ai-sdk go test ./internal/ucca/... -v"
```

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@@ -65,6 +65,7 @@ nav:
- Document Crawler:
- Uebersicht: services/document-crawler/index.md
- SDK Module:
- Vorbereitung-Module (Paket 1): services/sdk-modules/vorbereitung-module.md
- Analyse-Module (Paket 2): services/sdk-modules/analyse-module.md
- Dokumentations-Module (Paket 3+): services/sdk-modules/dokumentations-module.md
- DSFA (Art. 35 DSGVO): services/sdk-modules/dsfa.md