# ZUGFeRD-Service: Python REST API for Invoice Extraction and Validation

## TL;DR

> **Quick Summary**: Build a stateless FastAPI service that extracts structured data from ZUGFeRD/Factur-X invoices embedded in PDFs, validates invoice correctness, and is packaged for both Docker and NixOS deployment.
> 
> **Deliverables**:
> - Complete FastAPI application with 3 endpoints (`/health`, `/extract`, `/validate`)
> - Pydantic models for all request/response schemas
> - ZUGFeRD extraction pipeline using factur-x library
> - 4 validation checks (pflichtfelder, betraege, ustid, pdf_abgleich)
> - Docker multi-stage build (production-ready)
> - Nix flake packaging (buildPythonApplication)
> - Comprehensive test suite (TDD, pytest)
> - README documentation with installation guide
> 
> **Estimated Effort**: Medium-Large (20-30 tasks)
> **Parallel Execution**: YES - 4 waves
> **Critical Path**: Project Setup → Models → Extractor → Validator → API → Packaging

---

## Context

### Original Request
Build a Python-based REST API service for ZUGFeRD invoice extraction and validation. The service runs as a Docker container on NixOS and should also be packaged as a Nix flake. Key requirements include handling all ZUGFeRD profiles (MINIMUM through EXTENDED), validating invoice amounts and required fields, and comparing XML data against PDF text.

### Interview Summary
**Key Discussions**:
- **Framework choice**: FastAPI (user preference, excellent for REST APIs)
- **Project format**: pyproject.toml with hatchling (modern, Nix-friendly)
- **Nix packaging**: Flake-based approach with buildPythonApplication
- **Testing strategy**: TDD with pytest, source official sample PDFs
- **Authentication**: Open endpoints (no auth required)
- **File handling**: 10MB limit, reject password-protected PDFs
- **Calculations**: Standard rounding, 0.01 EUR tolerance

**Research Findings**:
- factur-x library provides `get_xml_from_pdf()`, `get_level()`, `get_flavor()` for extraction
- Nix packaging follows mem0 pattern: pyproject=true, pythonRelaxDeps=true
- UN/ECE unit codes require mapping dictionary (C62→Piece, KGM→Kilogram, etc.)
- ZUGFeRD profiles detected via GuidelineSpecifiedDocumentContextParameter in XML

### Metis Review
**Identified Gaps** (addressed):
- Password-protected PDFs → Reject with error
- File size limits → 10MB hard limit
- Decimal precision → Standard rounding
- Authentication → Confirmed open/stateless

---

## Work Objectives

### Core Objective
Create a production-ready, stateless REST API that extracts ZUGFeRD/Factur-X invoice data from PDFs, validates invoice correctness against business rules, and provides clear error reporting for invoice processing workflows.

### Concrete Deliverables
- `src/main.py` - FastAPI application with all endpoints
- `src/models.py` - Pydantic models for all data structures
- `src/extractor.py` - ZUGFeRD extraction logic
- `src/validator.py` - Validation checks implementation
- `src/pdf_parser.py` - PDF text extraction for cross-validation
- `src/utils.py` - Helper functions (unit codes, decimal handling)
- `pyproject.toml` - Project configuration with hatchling
- `Dockerfile` - Multi-stage production build
- `docker-compose.yml` - Local development setup
- `flake.nix` - Nix flake packaging
- `tests/` - Complete test suite with fixtures
- `README.md` - Installation and usage documentation

### Definition of Done
- [ ] `nix build .#zugferd-service` completes without errors
- [ ] `docker build -t zugferd-service .` produces image <500MB
- [ ] `pytest` runs all tests with 100% pass rate
- [ ] `curl http://localhost:5000/health` returns `{"status": "healthy", "version": "1.0.0"}`
- [ ] All ZUGFeRD profiles correctly detected from sample PDFs
- [ ] All validation checks produce expected errors/warnings

### Must Have
- All 3 API endpoints as specified
- Support for all ZUGFeRD profiles (MINIMUM, BASIC, BASIC WL, EN16931, EXTENDED)
- All 4 validation checks (pflichtfelder, betraege, ustid, pdf_abgleich)
- Structured JSON error responses with error codes
- UTF-8 encoding throughout
- Structured JSON logging

### Must NOT Have (Guardrails)
- ❌ Authentication middleware (open endpoints)
- ❌ Database or persistence layer (stateless only)
- ❌ Caching layers
- ❌ Rate limiting
- ❌ Metrics endpoints beyond /health
- ❌ CLI interface
- ❌ Web UI or admin dashboard
- ❌ Batch processing or queue system
- ❌ Online USt-ID validation (format check only)
- ❌ Support for ZUGFeRD 1.x (only 2.x)
- ❌ Abstraction layers for "future extensibility"

---

## Verification Strategy

> **UNIVERSAL RULE: ZERO HUMAN INTERVENTION**
>
> ALL tasks in this plan MUST be verifiable WITHOUT any human action.
> Every verification step is executed by the agent using tools (curl, pytest, nix, docker).

### Test Decision
- **Infrastructure exists**: NO (new project)
- **Automated tests**: TDD (test-first)
- **Framework**: pytest with pytest-asyncio

### TDD Workflow
Each implementation task follows RED-GREEN-REFACTOR:
1. **RED**: Write failing test first
2. **GREEN**: Implement minimum code to pass
3. **REFACTOR**: Clean up while keeping tests green

### Test Infrastructure Setup (Task 0)
```bash
# Install pytest and test dependencies
pip install pytest pytest-asyncio httpx

# Verify pytest works
pytest --version

# Run initial test
pytest tests/ -v
```

### Agent-Executed QA Scenarios (MANDATORY)

All verifications use:
- **API Testing**: `curl` commands with JSON assertions
- **Docker Testing**: `docker build` and `docker run` commands
- **Nix Testing**: `nix build` and `nix run` commands
- **Unit Testing**: `pytest` with specific test file targets

---

## Execution Strategy

### Parallel Execution Waves

```
Wave 1 (Start Immediately):
├── Task 1: Project scaffold (pyproject.toml, directories)
├── Task 2: Download ZUGFeRD sample PDFs
└── Task 3: Create Pydantic models

Wave 2 (After Wave 1):
├── Task 4: Extractor unit tests + implementation
├── Task 5: PDF parser unit tests + implementation
└── Task 6: Utils (unit codes, decimal handling)

Wave 3 (After Wave 2):
├── Task 7: Validator unit tests + implementation
├── Task 8: FastAPI app structure
└── Task 9: Health endpoint

Wave 4 (After Wave 3):
├── Task 10: Extract endpoint
├── Task 11: Validate endpoint
└── Task 12: Error handling middleware

Wave 5 (After Wave 4):
├── Task 13: Integration tests
├── Task 14: Dockerfile
└── Task 15: docker-compose.yml

Wave 6 (After Wave 5):
├── Task 16: Nix flake packaging
├── Task 17: NixOS module example
└── Task 18: README documentation

Critical Path: Task 1 → Task 4 → Task 7 → Task 10 → Task 13 → Task 16
```

### Dependency Matrix

| Task | Depends On | Blocks | Can Parallelize With |
|------|------------|--------|---------------------|
| 1 | None | 2-18 | None (must be first) |
| 2 | 1 | 4, 5 | 3 |
| 3 | 1 | 4, 5, 7 | 2 |
| 4 | 2, 3 | 7, 10 | 5, 6 |
| 5 | 2 | 7 | 4, 6 |
| 6 | 1 | 4, 7 | 4, 5 |
| 7 | 4, 5, 6 | 11 | 8, 9 |
| 8 | 3 | 9, 10, 11 | 7 |
| 9 | 8 | 10, 11 | 7 |
| 10 | 4, 8, 9 | 13 | 11, 12 |
| 11 | 7, 8, 9 | 13 | 10, 12 |
| 12 | 8 | 13 | 10, 11 |
| 13 | 10, 11, 12 | 14, 16 | None |
| 14 | 13 | 16 | 15 |
| 15 | 13 | None | 14 |
| 16 | 14 | 17, 18 | None |
| 17 | 16 | 18 | None |
| 18 | 16, 17 | None | None |

---

## TODOs

### Wave 1: Project Foundation

- [x] 1. Project Scaffold and Configuration

  **What to do**:
  - Create project directory structure as specified
  - Create `pyproject.toml` with hatchling build system
  - Configure pytest in pyproject.toml
  - Create `src/__init__.py` and `tests/__init__.py`
  - Set up Python version requirement (3.11+)

  **Must NOT do**:
  - Do NOT add optional dependencies
  - Do NOT create README yet (separate task)
  - Do NOT add pre-commit hooks

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Straightforward file creation with established patterns
  - **Skills**: [`git-master`]
    - `git-master`: For proper initial commit after scaffold

  **Parallelization**:
  - **Can Run In Parallel**: NO
  - **Parallel Group**: Sequential (must be first)
  - **Blocks**: All subsequent tasks
  - **Blocked By**: None

  **References**:
  - **Pattern References**: mem0 pyproject.toml pattern (from librarian research)
  - **External References**: https://hatch.pypa.io/latest/config/metadata/ (hatchling docs)

  **Files to Create**:
  ```
  pyproject.toml
  src/__init__.py
  src/main.py (placeholder)
  src/models.py (placeholder)
  src/extractor.py (placeholder)
  src/validator.py (placeholder)
  src/pdf_parser.py (placeholder)
  src/utils.py (placeholder)
  tests/__init__.py
  tests/conftest.py (pytest fixtures)
  tests/fixtures/.gitkeep
  ```

  **pyproject.toml Structure**:
  ```toml
  [build-system]
  requires = ["hatchling"]
  build-backend = "hatchling.build"

  [project]
  name = "zugferd-service"
  version = "1.0.0"
  description = "REST API for ZUGFeRD invoice extraction and validation"
  requires-python = ">=3.11"
  dependencies = [
      "fastapi>=0.109.0",
      "uvicorn>=0.27.0",
      "python-multipart>=0.0.6",
      "factur-x>=2.5",
      "pypdf>=4.0.0",
      "pydantic>=2.5.0",
      "lxml>=5.0.0",
  ]

  [project.optional-dependencies]
  dev = [
      "pytest>=8.0.0",
      "pytest-asyncio>=0.23.0",
      "httpx>=0.27.0",
  ]

  [project.scripts]
  zugferd-service = "src.main:run"

  [tool.pytest.ini_options]
  asyncio_mode = "auto"
  testpaths = ["tests"]
  ```

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: pyproject.toml is valid
    Tool: Bash
    Steps:
      1. python -c "import tomllib; tomllib.load(open('pyproject.toml', 'rb'))"
      2. Assert: Exit code 0
    Expected Result: TOML parses without error
    Evidence: Command output captured

  Scenario: Project structure exists
    Tool: Bash
    Steps:
      1. ls -la src/
      2. Assert: main.py, models.py, extractor.py, validator.py, pdf_parser.py, utils.py exist
      3. ls -la tests/
      4. Assert: conftest.py, fixtures/ exist
    Expected Result: All required files present
    Evidence: Directory listing captured

  Scenario: Dependencies install correctly
    Tool: Bash
    Steps:
      1. pip install -e ".[dev]"
      2. Assert: Exit code 0
      3. python -c "import fastapi; import facturx; import pypdf"
      4. Assert: Exit code 0
    Expected Result: All dependencies importable
    Evidence: pip output captured
  ```

  **Commit**: YES
  - Message: `feat(project): initialize ZUGFeRD service with pyproject.toml and directory structure`
  - Files: All created files
  - Pre-commit: `python -c "import tomllib; tomllib.load(open('pyproject.toml', 'rb'))"`

---

- [x] 2. Download ZUGFeRD Sample PDFs

  **What to do**:
  - Download official ZUGFeRD sample PDFs from FeRD/ZUGFeRD repositories
  - Include samples for: MINIMUM, BASIC, BASIC WL, EN16931, EXTENDED profiles
  - Include a non-ZUGFeRD PDF for negative testing
  - Store in `tests/fixtures/`
  - Create fixture manifest documenting each file

  **Must NOT do**:
  - Do NOT create synthetic PDFs
  - Do NOT download more than 10 samples (keep focused)

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Download and organize files
  - **Skills**: []
    - No special skills needed

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 1 (with Task 3)
  - **Blocks**: Tasks 4, 5
  - **Blocked By**: Task 1

  **References**:
  - **External References**: 
    - https://www.ferd-net.de/download/testrechnungen
    - https://github.com/ZUGFeRD/mustangproject/tree/master/Mustang-CLI/src/test/resources
    - https://github.com/akretion/factur-x/tree/master/tests

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Sample PDFs exist for all profiles
    Tool: Bash
    Steps:
      1. ls tests/fixtures/*.pdf | wc -l
      2. Assert: At least 5 PDF files
      3. file tests/fixtures/*.pdf
      4. Assert: All files identified as "PDF document"
    Expected Result: Multiple valid PDF files in fixtures
    Evidence: File listing captured

  Scenario: Fixture manifest documents samples
    Tool: Bash
    Steps:
      1. cat tests/fixtures/MANIFEST.md
      2. Assert: Contains entries for MINIMUM, BASIC, EN16931, EXTENDED
    Expected Result: Manifest describes all test fixtures
    Evidence: Manifest content captured
  ```

  **Commit**: YES
  - Message: `test(fixtures): add official ZUGFeRD sample PDFs for all profiles`
  - Files: `tests/fixtures/*.pdf`, `tests/fixtures/MANIFEST.md`

---

- [x] 3. Create Pydantic Models

  **What to do**:
  - Define all Pydantic models as per API specification
  - Models: ExtractRequest, ExtractResponse, ValidateRequest, ValidateResponse
  - Nested models: Supplier, Buyer, LineItem, Totals, VatBreakdown, PaymentTerms
  - Error models: ErrorResponse, ValidationError
  - Add field validators where appropriate (e.g., VAT ID format)

  **Must NOT do**:
  - Do NOT add ORM mappings (no database)
  - Do NOT add serialization beyond Pydantic defaults

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Straightforward Pydantic model definitions from spec
  - **Skills**: []
    - Standard Python work

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 1 (with Task 2)
  - **Blocks**: Tasks 4, 5, 7
  - **Blocked By**: Task 1

  **References**:
  - **API Specification**: User's detailed spec document (request/response schemas)
  - **Pattern References**: https://docs.pydantic.dev/latest/concepts/models/
  
  **Key Models from Spec**:
  ```python
  class Supplier(BaseModel):
      name: str
      street: str | None = None
      postal_code: str | None = None
      city: str | None = None
      country: str | None = None
      vat_id: str | None = None
      email: str | None = None

  class LineItem(BaseModel):
      position: int
      article_number: str | None = None
      article_number_buyer: str | None = None
      description: str
      quantity: float
      unit: str  # Human-readable, translated from UN/ECE code
      unit_price: float
      line_total: float
      vat_rate: float | None = None
      vat_amount: float | None = None

  class ExtractResponse(BaseModel):
      is_zugferd: bool
      zugferd_profil: str | None = None
      xml_raw: str | None = None
      xml_data: XmlData | None = None
      pdf_text: str | None = None
      extraction_meta: ExtractionMeta
  ```

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  # tests/test_models.py
  def test_extract_response_zugferd():
      response = ExtractResponse(
          is_zugferd=True,
          zugferd_profil="EN16931",
          xml_raw="<?xml ...",
          # ... full data
      )
      assert response.is_zugferd is True
      assert response.zugferd_profil == "EN16931"

  def test_extract_response_non_zugferd():
      response = ExtractResponse(
          is_zugferd=False,
          pdf_text="Invoice text...",
          extraction_meta=ExtractionMeta(pages=1, extraction_time_ms=50)
      )
      assert response.xml_data is None

  def test_line_item_validation():
      item = LineItem(
          position=1,
          description="Widget",
          quantity=10.0,
          unit="Piece",
          unit_price=9.99,
          line_total=99.90
      )
      assert item.line_total == 99.90
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Models pass all unit tests
    Tool: Bash
    Steps:
      1. pytest tests/test_models.py -v
      2. Assert: All tests pass (exit code 0)
    Expected Result: 100% test pass rate
    Evidence: pytest output captured

  Scenario: Models serialize to JSON correctly
    Tool: Bash
    Steps:
      1. python -c "from src.models import ExtractResponse, ExtractionMeta; r = ExtractResponse(is_zugferd=False, extraction_meta=ExtractionMeta(pages=1, extraction_time_ms=50)); print(r.model_dump_json())"
      2. Assert: Valid JSON output containing "is_zugferd": false
    Expected Result: JSON serialization works
    Evidence: JSON output captured
  ```

  **Commit**: YES
  - Message: `feat(models): add Pydantic models for all API request/response schemas`
  - Files: `src/models.py`, `tests/test_models.py`
  - Pre-commit: `pytest tests/test_models.py`

---

### Wave 2: Core Extraction Logic

- [x] 4. ZUGFeRD Extractor Implementation (TDD)

  **What to do**:
  - Write tests first using sample PDFs from fixtures
  - Implement `extract_zugferd()` function using factur-x library
  - Handle profile detection (get_level, get_flavor)
  - Parse XML to structured data matching models
  - Handle non-ZUGFeRD PDFs gracefully
  - Handle errors (corrupt PDF, password-protected)

  **Must NOT do**:
  - Do NOT implement custom XML parsing if factur-x provides it
  - Do NOT cache extracted data

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Core business logic requiring careful implementation
  - **Skills**: [`systematic-debugging`]
    - `systematic-debugging`: For handling edge cases in PDF extraction

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 2 (with Tasks 5, 6)
  - **Blocks**: Tasks 7, 10
  - **Blocked By**: Tasks 2, 3

  **References**:
  - **Library Docs**: https://github.com/akretion/factur-x
  - **Pattern References**: factur-x get_xml_from_pdf usage (from librarian research)
  - **Test Fixtures**: `tests/fixtures/*.pdf`

  **Key Functions**:
  ```python
  from facturx import get_xml_from_pdf, get_level, get_flavor

  def extract_zugferd(pdf_bytes: bytes) -> ExtractResponse:
      """Extract ZUGFeRD data from PDF bytes."""
      # 1. Check file size (<10MB)
      # 2. Try to extract XML using factur-x
      # 3. Detect profile and flavor
      # 4. Parse XML to structured data
      # 5. Extract PDF text for pdf_abgleich
      # 6. Return ExtractResponse
  ```

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  # tests/test_extractor.py
  def test_extract_en16931_profile(sample_en16931_pdf):
      result = extract_zugferd(sample_en16931_pdf)
      assert result.is_zugferd is True
      assert result.zugferd_profil == "EN16931"
      assert result.xml_data is not None
      assert result.xml_data.invoice_number is not None

  def test_extract_non_zugferd_pdf(sample_plain_pdf):
      result = extract_zugferd(sample_plain_pdf)
      assert result.is_zugferd is False
      assert result.xml_data is None
      assert result.pdf_text is not None

  def test_extract_corrupt_pdf():
      with pytest.raises(ExtractionError) as exc:
          extract_zugferd(b"not a pdf")
      assert exc.value.error_code == "invalid_pdf"

  def test_file_size_limit():
      large_pdf = b"x" * (11 * 1024 * 1024)  # 11MB
      with pytest.raises(ExtractionError) as exc:
          extract_zugferd(large_pdf)
      assert exc.value.error_code == "file_too_large"
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Extractor passes all unit tests
    Tool: Bash
    Steps:
      1. pytest tests/test_extractor.py -v
      2. Assert: All tests pass
    Expected Result: 100% test pass rate
    Evidence: pytest output captured

  Scenario: EN16931 profile correctly detected
    Tool: Bash
    Steps:
      1. python -c "
         from src.extractor import extract_zugferd
         with open('tests/fixtures/sample_en16931.pdf', 'rb') as f:
             result = extract_zugferd(f.read())
         print(f'Profile: {result.zugferd_profil}')
         print(f'Invoice: {result.xml_data.invoice_number}')"
      2. Assert: Output contains "Profile: EN16931" or "Profile: en16931"
    Expected Result: Profile correctly identified
    Evidence: Script output captured

  Scenario: Non-ZUGFeRD PDF handled gracefully
    Tool: Bash
    Steps:
      1. python -c "
         from src.extractor import extract_zugferd
         with open('tests/fixtures/sample_no_zugferd.pdf', 'rb') as f:
             result = extract_zugferd(f.read())
         assert result.is_zugferd == False
         assert result.pdf_text is not None
         print('OK: Non-ZUGFeRD handled correctly')"
      2. Assert: Output contains "OK:"
    Expected Result: Graceful handling
    Evidence: Script output captured
  ```

  **Commit**: YES
  - Message: `feat(extractor): implement ZUGFeRD extraction with profile detection`
  - Files: `src/extractor.py`, `tests/test_extractor.py`
  - Pre-commit: `pytest tests/test_extractor.py`

---

- [x] 5. PDF Text Parser Implementation (TDD)

  **What to do**:
  - Write tests first with expected extraction patterns
  - Implement PDF text extraction using pypdf
  - Create regex patterns for extracting key values from text
  - Extract: invoice_number, invoice_date, amounts (net, gross, vat)
  - Return confidence scores for each extraction

  **Must NOT do**:
  - Do NOT use OCR (text extraction only)
  - Do NOT parse images in PDFs

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Regex pattern development requires careful testing
  - **Skills**: [`systematic-debugging`]
    - `systematic-debugging`: For developing and testing regex patterns

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 2 (with Tasks 4, 6)
  - **Blocks**: Task 7
  - **Blocked By**: Task 2

  **References**:
  - **User Spec**: Regex patterns provided in spec (invoice_number, gross_amount patterns)
  - **Library Docs**: https://pypdf.readthedocs.io/en/stable/

  **Key Patterns from Spec**:
  ```python
  EXTRACTION_PATTERNS = {
      "invoice_number": [
          r"Rechnungs?-?(?:Nr|Nummer)[.:\s]*([A-Z0-9\-]+)",
          r"Invoice\s*(?:No|Number)?[.:\s]*([A-Z0-9\-]+)",
          r"Beleg-?Nr[.:\s]*([A-Z0-9\-]+)"
      ],
      "gross_amount": [
          r"Brutto[:\s]*([0-9.,]+)\s*(?:EUR|€)?",
          r"Gesamtbetrag[:\s]*([0-9.,]+)",
          r"Total[:\s]*([0-9.,]+)\s*(?:EUR|€)?"
      ],
      # ... more patterns
  }
  ```

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  # tests/test_pdf_parser.py
  def test_extract_invoice_number():
      text = "Rechnung\nRechnungs-Nr.: RE-2025-001234\nDatum: 04.02.2025"
      result = extract_from_text(text)
      assert result["invoice_number"] == "RE-2025-001234"
      assert result["invoice_number_confidence"] >= 0.9

  def test_extract_amounts():
      text = "Netto: 100,00 EUR\nMwSt 19%: 19,00 EUR\nBrutto: 119,00 EUR"
      result = extract_from_text(text)
      assert result["gross_amount"] == 119.00
      assert result["net_amount"] == 100.00

  def test_german_number_format():
      text = "Gesamtbetrag: 1.234,56 €"
      result = extract_from_text(text)
      assert result["gross_amount"] == 1234.56
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: PDF parser passes all unit tests
    Tool: Bash
    Steps:
      1. pytest tests/test_pdf_parser.py -v
      2. Assert: All tests pass
    Expected Result: 100% test pass rate
    Evidence: pytest output captured

  Scenario: Real PDF text extraction works
    Tool: Bash
    Steps:
      1. python -c "
         from src.pdf_parser import extract_text_from_pdf, extract_from_text
         with open('tests/fixtures/sample_en16931.pdf', 'rb') as f:
             text = extract_text_from_pdf(f.read())
         print(f'Extracted {len(text)} characters')
         result = extract_from_text(text)
         print(f'Invoice: {result.get(\"invoice_number\", \"NOT FOUND\")}')"
      2. Assert: Output shows extracted characters and invoice number
    Expected Result: Text extraction works on real PDFs
    Evidence: Script output captured
  ```

  **Commit**: YES
  - Message: `feat(pdf-parser): implement PDF text extraction with regex patterns`
  - Files: `src/pdf_parser.py`, `tests/test_pdf_parser.py`
  - Pre-commit: `pytest tests/test_pdf_parser.py`

---

- [x] 6. Utility Functions Implementation

  **What to do**:
  - Create UN/ECE unit code mapping dictionary
  - Implement decimal rounding helper (2 decimal places, standard rounding)
  - Implement tolerance comparison function (0.01 EUR)
  - Add German date format parser

  **Must NOT do**:
  - Do NOT create configurable tolerance (hardcode 0.01)
  - Do NOT add unit codes beyond common ones (expand later if needed)

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Simple utility functions
  - **Skills**: []
    - Standard Python work

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 2 (with Tasks 4, 5)
  - **Blocks**: Tasks 4, 7
  - **Blocked By**: Task 1

  **References**:
  - **UN/ECE Codes**: https://docs.peppol.eu/poacc/upgrade-3/codelist/UNECERec20/

  **Unit Code Dictionary**:
  ```python
  UNECE_UNIT_CODES = {
      "C62": "Stück",
      "H87": "Stück",
      "KGM": "Kilogramm",
      "GRM": "Gramm",
      "TNE": "Tonne",
      "MTR": "Meter",
      "KMT": "Kilometer",
      "MTK": "Quadratmeter",
      "LTR": "Liter",
      "MLT": "Milliliter",
      "DAY": "Tag",
      "HUR": "Stunde",
      "MON": "Monat",
      "ANN": "Jahr",
      "SET": "Set",
      "PCE": "Stück",
      "EA": "Stück",
  }
  ```

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Unit code translation works
    Tool: Bash
    Steps:
      1. python -c "
         from src.utils import translate_unit_code
         assert translate_unit_code('C62') == 'Stück'
         assert translate_unit_code('KGM') == 'Kilogramm'
         assert translate_unit_code('UNKNOWN') == 'UNKNOWN'
         print('OK: Unit codes translate correctly')"
      2. Assert: Output contains "OK:"
    Expected Result: All translations correct
    Evidence: Script output captured

  Scenario: Decimal comparison with tolerance
    Tool: Bash
    Steps:
      1. python -c "
         from src.utils import amounts_match
         assert amounts_match(100.00, 100.00) == True
         assert amounts_match(100.00, 100.005) == True  # Within 0.01
         assert amounts_match(100.00, 100.02) == False  # Outside tolerance
         print('OK: Tolerance comparison works')"
      2. Assert: Output contains "OK:"
    Expected Result: Tolerance logic correct
    Evidence: Script output captured
  ```

  **Commit**: YES
  - Message: `feat(utils): add unit code mapping and decimal utilities`
  - Files: `src/utils.py`, `tests/test_utils.py`
  - Pre-commit: `pytest tests/test_utils.py`

---

### Wave 3: Validation Logic

- [x] 7. Validator Implementation (TDD)

  **What to do**:
  - Write tests first for each validation check
  - Implement all 4 validation checks:
    1. `pflichtfelder` - Required fields check
    2. `betraege` - Amount calculations check
    3. `ustid` - VAT ID format check
    4. `pdf_abgleich` - XML vs PDF comparison
  - Return structured ValidationResult with errors and warnings

  **Must NOT do**:
  - Do NOT implement online USt-ID validation
  - Do NOT add validation checks beyond spec

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Core business logic with multiple validation rules
  - **Skills**: [`systematic-debugging`]
    - `systematic-debugging`: For handling edge cases in validation logic

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 3 (with Tasks 8, 9)
  - **Blocks**: Task 11
  - **Blocked By**: Tasks 4, 5, 6

  **References**:
  - **User Spec**: Detailed validation logic tables
  - **Pattern References**: src/models.py ValidationError model

  **Validation Rules from Spec**:

  **pflichtfelder (Required Fields)**:
  | Field | Severity |
  |-------|----------|
  | invoice_number | critical |
  | invoice_date | critical |
  | supplier.name | critical |
  | supplier.vat_id | critical |
  | buyer.name | critical |
  | totals.net | critical |
  | totals.gross | critical |
  | totals.vat_total | critical |
  | due_date | warning |
  | payment_terms.iban | warning |
  | line_items (min 1) | critical |

  **betraege (Calculations)**:
  - line_total ≈ quantity × unit_price (±0.01)
  - totals.net ≈ Σ(line_items.line_total) (±0.01)
  - vat_breakdown.amount ≈ base × (rate/100) (±0.01)
  - totals.vat_total ≈ Σ(vat_breakdown.amount) (±0.01)
  - totals.gross ≈ totals.net + totals.vat_total (±0.01)

  **ustid (VAT ID Format)**:
  | Country | Regex |
  |---------|-------|
  | DE | `^DE[0-9]{9}$` |
  | AT | `^ATU[0-9]{8}$` |
  | CH | `^CHE[0-9]{9}(MWST\|TVA\|IVA)$` |

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  # tests/test_validator.py
  def test_pflichtfelder_missing_invoice_number():
      data = XmlData(invoice_number=None, ...)
      result = validate_pflichtfelder(data)
      assert any(e.field == "invoice_number" for e in result.errors)
      assert any(e.severity == "critical" for e in result.errors)

  def test_betraege_calculation_mismatch():
      data = XmlData(
          line_items=[LineItem(quantity=10, unit_price=9.99, line_total=100.00)],  # Wrong!
          ...
      )
      result = validate_betraege(data)
      assert any(e.error_code == "calculation_mismatch" for e in result.errors)
      assert any("99.90" in e.message for e in result.errors)

  def test_ustid_valid_german():
      result = validate_ustid("DE123456789")
      assert result.is_valid is True

  def test_ustid_invalid_format():
      result = validate_ustid("DE12345")  # Too short
      assert result.is_valid is False
      assert result.error_code == "invalid_format"

  def test_pdf_abgleich_mismatch():
      xml_data = XmlData(invoice_number="RE-001", totals=Totals(gross=118.88))
      pdf_values = {"invoice_number": "RE-002", "gross_amount": 118.88}
      result = validate_pdf_abgleich(xml_data, pdf_values)
      assert any(e.field == "invoice_number" for e in result.errors)
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Validator passes all unit tests
    Tool: Bash
    Steps:
      1. pytest tests/test_validator.py -v
      2. Assert: All tests pass
    Expected Result: 100% test pass rate
    Evidence: pytest output captured

  Scenario: All validation checks work together
    Tool: Bash
    Steps:
      1. python -c "
         from src.validator import validate_invoice
         from src.models import XmlData, ValidateRequest
         # Create a request with known issues
         request = ValidateRequest(
             xml_data={'invoice_number': None, ...},
             checks=['pflichtfelder', 'betraege']
         )
         result = validate_invoice(request)
         print(f'Errors: {len(result.errors)}')"
      2. Assert: Script runs without error, shows error count
    Expected Result: Validator processes all checks
    Evidence: Script output captured
  ```

  **Commit**: YES
  - Message: `feat(validator): implement all validation checks (pflichtfelder, betraege, ustid, pdf_abgleich)`
  - Files: `src/validator.py`, `tests/test_validator.py`
  - Pre-commit: `pytest tests/test_validator.py`

---

### Wave 3 (continued): API Foundation

- [x] 8. FastAPI Application Structure

  **What to do**:
  - Create FastAPI app instance in main.py
  - Configure exception handlers for custom errors
  - Set up structured JSON logging
  - Add CORS middleware (for local development)
  - Configure app metadata (title, version, description)

  **Must NOT do**:
  - Do NOT add authentication middleware
  - Do NOT add rate limiting

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Standard FastAPI setup
  - **Skills**: []
    - Standard FastAPI patterns

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 3 (with Tasks 7, 9)
  - **Blocks**: Tasks 9, 10, 11
  - **Blocked By**: Task 3

  **References**:
  - **FastAPI Docs**: https://fastapi.tiangolo.com/
  - **Pattern References**: User spec error handling table

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: FastAPI app starts
    Tool: Bash
    Steps:
      1. timeout 5 uvicorn src.main:app --port 5001 &
      2. sleep 2
      3. curl -s http://localhost:5001/openapi.json | head -c 100
      4. Assert: Output contains "openapi"
      5. kill %1
    Expected Result: OpenAPI schema accessible
    Evidence: curl output captured
  ```

  **Commit**: YES
  - Message: `feat(api): create FastAPI application structure with error handling`
  - Files: `src/main.py`
  - Pre-commit: `python -c "from src.main import app; print(app.title)"`

---

- [x] 9. Health Endpoint Implementation

  **What to do**:
  - Implement `GET /health` endpoint
  - Return version from pyproject.toml
  - Return simple health status

  **Must NOT do**:
  - Do NOT add complex health checks (no dependencies to check)

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Simple endpoint
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 3 (with Tasks 7, 8)
  - **Blocks**: Tasks 10, 11
  - **Blocked By**: Task 8

  **References**:
  - **User Spec**: Health endpoint response format

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Health endpoint returns correct format
    Tool: Bash
    Steps:
      1. uvicorn src.main:app --port 5002 &
      2. sleep 2
      3. curl -s http://localhost:5002/health
      4. Assert: Response contains {"status": "healthy", "version": "1.0.0"}
      5. kill %1
    Expected Result: Health check passes
    Evidence: curl output captured
  ```

  **Commit**: YES (groups with Task 8)
  - Message: `feat(api): add health endpoint`
  - Files: `src/main.py`

---

### Wave 4: API Endpoints

- [x] 10. Extract Endpoint Implementation (TDD)

  **What to do**:
  - Write integration tests for `/extract` endpoint
  - Implement `POST /extract` endpoint
  - Accept base64-encoded PDF in JSON body
  - Use extractor module for extraction
  - Return structured ExtractResponse

  **Must NOT do**:
  - Do NOT accept multipart file uploads (JSON only per spec)

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Integration of extractor into API endpoint
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 4 (with Tasks 11, 12)
  - **Blocks**: Task 13
  - **Blocked By**: Tasks 4, 8, 9

  **References**:
  - **User Spec**: /extract request/response format
  - **Pattern References**: src/extractor.py

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  # tests/test_api.py
  @pytest.fixture
  def client():
      return TestClient(app)

  def test_extract_zugferd_pdf(client, sample_en16931_pdf_base64):
      response = client.post("/extract", json={"pdf_base64": sample_en16931_pdf_base64})
      assert response.status_code == 200
      data = response.json()
      assert data["is_zugferd"] is True
      assert data["zugferd_profil"] is not None

  def test_extract_invalid_base64(client):
      response = client.post("/extract", json={"pdf_base64": "not-valid-base64!!!"})
      assert response.status_code == 400
      assert response.json()["error"] == "invalid_base64"

  def test_extract_non_pdf(client):
      # Base64 of "Hello World" (not a PDF)
      response = client.post("/extract", json={"pdf_base64": "SGVsbG8gV29ybGQ="})
      assert response.status_code == 400
      assert response.json()["error"] == "invalid_pdf"
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Extract endpoint integration test
    Tool: Bash
    Steps:
      1. pytest tests/test_api.py::test_extract -v
      2. Assert: All extract tests pass
    Expected Result: Endpoint works correctly
    Evidence: pytest output captured

  Scenario: Live extract endpoint test
    Tool: Bash
    Steps:
      1. uvicorn src.main:app --port 5003 &
      2. sleep 2
      3. PDF_BASE64=$(base64 -w 0 tests/fixtures/sample_en16931.pdf)
      4. curl -s -X POST http://localhost:5003/extract \
           -H "Content-Type: application/json" \
           -d "{\"pdf_base64\": \"$PDF_BASE64\"}" | jq '.is_zugferd'
      5. Assert: Output is "true"
      6. kill %1
    Expected Result: ZUGFeRD detected
    Evidence: curl output captured
  ```

  **Commit**: YES
  - Message: `feat(api): implement /extract endpoint for PDF processing`
  - Files: `src/main.py`, `tests/test_api.py`
  - Pre-commit: `pytest tests/test_api.py::test_extract`

---

- [x] 11. Validate Endpoint Implementation (TDD)

  **What to do**:
  - Write integration tests for `/validate` endpoint
  - Implement `POST /validate` endpoint
  - Accept xml_data, pdf_text, and checks array
  - Use validator module for validation
  - Return structured ValidateResponse

  **Must NOT do**:
  - Do NOT run checks not in the request's checks array

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Integration of validator into API endpoint
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 4 (with Tasks 10, 12)
  - **Blocks**: Task 13
  - **Blocked By**: Tasks 7, 8, 9

  **References**:
  - **User Spec**: /validate request/response format
  - **Pattern References**: src/validator.py

  **Acceptance Criteria**:

  **TDD - Write Tests First:**
  ```python
  def test_validate_all_checks(client):
      response = client.post("/validate", json={
          "xml_data": {...},
          "pdf_text": "...",
          "checks": ["pflichtfelder", "betraege", "ustid", "pdf_abgleich"]
      })
      assert response.status_code == 200
      data = response.json()
      assert "is_valid" in data
      assert "errors" in data
      assert "summary" in data

  def test_validate_partial_checks(client):
      response = client.post("/validate", json={
          "xml_data": {...},
          "checks": ["pflichtfelder"]
      })
      assert response.status_code == 200
      # Only pflichtfelder check should run
  ```

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Validate endpoint integration test
    Tool: Bash
    Steps:
      1. pytest tests/test_api.py::test_validate -v
      2. Assert: All validate tests pass
    Expected Result: Endpoint works correctly
    Evidence: pytest output captured

  Scenario: Live validate endpoint with invalid data
    Tool: Bash
    Steps:
      1. uvicorn src.main:app --port 5004 &
      2. sleep 2
      3. curl -s -X POST http://localhost:5004/validate \
           -H "Content-Type: application/json" \
           -d '{"xml_data": {"invoice_number": null}, "checks": ["pflichtfelder"]}' | jq '.is_valid'
      4. Assert: Output is "false"
      5. kill %1
    Expected Result: Validation detects missing field
    Evidence: curl output captured
  ```

  **Commit**: YES
  - Message: `feat(api): implement /validate endpoint for invoice validation`
  - Files: `src/main.py`, `tests/test_api.py`
  - Pre-commit: `pytest tests/test_api.py::test_validate`

---

- [x] 12. Error Handling Middleware

  **What to do**:
  - Implement exception handlers for all error types
  - Map exceptions to HTTP status codes and error responses
  - Ensure all errors return JSON format
  - Add request logging

  **Must NOT do**:
  - Do NOT expose stack traces in production

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Standard FastAPI error handling
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 4 (with Tasks 10, 11)
  - **Blocks**: Task 13
  - **Blocked By**: Task 8

  **References**:
  - **User Spec**: Error handling table

  **Error Mapping from Spec**:
  | Error | Status | error_code |
  |-------|--------|------------|
  | Invalid JSON | 400 | invalid_json |
  | Not a PDF | 400 | invalid_pdf |
  | PDF corrupt | 400 | corrupt_pdf |
  | Base64 invalid | 400 | invalid_base64 |
  | File too large | 400 | file_too_large |
  | Password protected | 400 | password_protected_pdf |
  | Internal error | 500 | internal_error |

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Error responses are JSON
    Tool: Bash
    Steps:
      1. uvicorn src.main:app --port 5005 &
      2. sleep 2
      3. curl -s -X POST http://localhost:5005/extract \
           -H "Content-Type: application/json" \
           -d '{"pdf_base64": "invalid!!!"}' | jq '.error'
      4. Assert: Output is "invalid_base64"
      5. kill %1
    Expected Result: JSON error response
    Evidence: curl output captured
  ```

  **Commit**: YES (groups with Task 10, 11)
  - Message: `feat(api): add comprehensive error handling middleware`
  - Files: `src/main.py`

---

### Wave 5: Packaging

- [x] 13. Integration Tests

  **What to do**:
  - Create end-to-end integration tests
  - Test full workflow: extract → validate
  - Test with all sample PDFs
  - Test error scenarios

  **Must NOT do**:
  - Do NOT create performance tests

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Integration testing requires comprehensive coverage
  - **Skills**: [`systematic-debugging`]

  **Parallelization**:
  - **Can Run In Parallel**: NO
  - **Parallel Group**: Sequential (depends on all endpoints)
  - **Blocks**: Tasks 14, 16
  - **Blocked By**: Tasks 10, 11, 12

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Full integration test suite passes
    Tool: Bash
    Steps:
      1. pytest tests/ -v --tb=short
      2. Assert: All tests pass (exit code 0)
    Expected Result: 100% test pass rate
    Evidence: pytest output captured
  ```

  **Commit**: YES
  - Message: `test(integration): add end-to-end integration tests`
  - Files: `tests/test_integration.py`
  - Pre-commit: `pytest tests/`

---

- [x] 14. Dockerfile Creation

  **What to do**:
  - Create multi-stage Dockerfile as per spec
  - Build stage: install dependencies
  - Production stage: slim image with app
  - Non-root user for security
  - Expose port 5000

  **Must NOT do**:
  - Do NOT include dev dependencies in production image

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Standard Dockerfile from spec template
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 5 (with Task 15)
  - **Blocks**: Task 16
  - **Blocked By**: Task 13

  **References**:
  - **User Spec**: Complete Dockerfile template provided

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Docker build succeeds
    Tool: Bash
    Steps:
      1. docker build -t zugferd-service:test .
      2. Assert: Exit code 0
      3. docker images zugferd-service:test --format "{{.Size}}"
      4. Assert: Size < 500MB
    Expected Result: Image builds and is reasonably sized
    Evidence: Build output captured

  Scenario: Container runs and responds
    Tool: Bash
    Steps:
      1. docker run -d --name zugferd-test -p 5006:5000 zugferd-service:test
      2. sleep 3
      3. curl -s http://localhost:5006/health | jq '.status'
      4. Assert: Output is "healthy"
      5. docker stop zugferd-test && docker rm zugferd-test
    Expected Result: Container is functional
    Evidence: curl output captured
  ```

  **Commit**: YES
  - Message: `build(docker): add multi-stage Dockerfile for production`
  - Files: `Dockerfile`
  - Pre-commit: `docker build -t zugferd-service:test .`

---

- [x] 15. Docker Compose Configuration

  **What to do**:
  - Create docker-compose.yml for local development
  - Include volume mount for live reload
  - Configure environment variables
  - Add health check

  **Must NOT do**:
  - Do NOT add additional services (no DB, no cache)

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Simple docker-compose setup
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: YES
  - **Parallel Group**: Wave 5 (with Task 14)
  - **Blocks**: None
  - **Blocked By**: Task 13

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Docker Compose starts service
    Tool: Bash
    Steps:
      1. docker-compose up -d
      2. sleep 5
      3. curl -s http://localhost:5000/health | jq '.status'
      4. Assert: Output is "healthy"
      5. docker-compose down
    Expected Result: Compose setup works
    Evidence: curl output captured
  ```

  **Commit**: YES
  - Message: `build(docker): add docker-compose.yml for local development`
  - Files: `docker-compose.yml`

---

### Wave 6: Nix Packaging

- [ ] 16. Nix Flake Packaging

  **What to do**:
  - Create flake.nix with buildPythonApplication
  - Use pythonRelaxDeps for dependency flexibility
  - Include devShell for development
  - Test with nix build and nix run

  **Must NOT do**:
  - Do NOT create complex overlay structure

  **Recommended Agent Profile**:
  - **Category**: `unspecified-high`
    - Reason: Nix packaging requires careful dependency handling
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: NO
  - **Parallel Group**: Sequential
  - **Blocks**: Tasks 17, 18
  - **Blocked By**: Task 14

  **References**:
  - **Librarian Research**: mem0 Nix packaging pattern
  - **External References**: https://github.com/mem0ai/mem0 Nix package

  **flake.nix Structure**:
  ```nix
  {
    description = "ZUGFeRD REST API Service";

    inputs = {
      nixpkgs.url = "github:NixOS/nixpkgs/nixos-unstable";
      flake-utils.url = "github:numtide/flake-utils";
    };

    outputs = { self, nixpkgs, flake-utils }:
      flake-utils.lib.eachDefaultSystem (system:
        let
          pkgs = nixpkgs.legacyPackages.${system};
          pythonPackages = pkgs.python311Packages;

          zugferd-service = pythonPackages.buildPythonApplication {
            pname = "zugferd-service";
            version = "1.0.0";
            pyproject = true;
            src = ./.;

            pythonRelaxDeps = true;

            build-system = [ pythonPackages.hatchling ];

            dependencies = with pythonPackages; [
              fastapi
              uvicorn
              pydantic
              python-multipart
              # factur-x - may need packaging
              pypdf
              lxml
            ];

            nativeCheckInputs = with pythonPackages; [
              pytestCheckHook
              pytest-asyncio
              httpx
            ];

            passthru = {
              mainProgram = "zugferd-service";
            };

            meta = {
              description = "REST API for ZUGFeRD invoice extraction";
              license = pkgs.lib.licenses.mit;
            };
          };
        in
        {
          packages.default = zugferd-service;
          packages.zugferd-service = zugferd-service;

          devShells.default = pkgs.mkShell {
            packages = [
              (pkgs.python311.withPackages (ps: with ps; [
                fastapi uvicorn pydantic pypdf lxml
                pytest pytest-asyncio httpx
              ]))
            ];
          };
        }
      );
  }
  ```

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: Nix flake builds successfully
    Tool: Bash
    Steps:
      1. nix build .#zugferd-service
      2. Assert: Exit code 0
      3. ls -la result/bin/
      4. Assert: zugferd-service binary exists
    Expected Result: Nix package builds
    Evidence: Build output captured

  Scenario: Nix package runs correctly
    Tool: Bash
    Steps:
      1. nix run .#zugferd-service &
      2. sleep 3
      3. curl -s http://localhost:5000/health | jq '.status'
      4. Assert: Output is "healthy"
      5. kill %1
    Expected Result: Nix-built service runs
    Evidence: curl output captured

  Scenario: Dev shell provides dependencies
    Tool: Bash
    Steps:
      1. nix develop -c python -c "import fastapi; import pypdf; print('OK')"
      2. Assert: Output is "OK"
    Expected Result: Dev shell has all deps
    Evidence: Command output captured
  ```

  **Commit**: YES
  - Message: `build(nix): add flake.nix for Nix packaging`
  - Files: `flake.nix`
  - Pre-commit: `nix flake check`

---

- [ ] 17. NixOS Service Module Example

  **What to do**:
  - Create example NixOS module for deployment
  - Include service configuration options
  - Add systemd service definition
  - Document usage in README

  **Must NOT do**:
  - Do NOT create production-ready module (example only)

  **Recommended Agent Profile**:
  - **Category**: `quick`
    - Reason: Example module following standard patterns
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: NO
  - **Parallel Group**: Sequential
  - **Blocks**: Task 18
  - **Blocked By**: Task 16

  **References**:
  - **User Spec**: NixOS container configuration example
  - **Librarian Research**: NixOS service module pattern

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: NixOS module syntax is valid
    Tool: Bash
    Steps:
      1. nix-instantiate --eval -E "import ./nix/module.nix"
      2. Assert: Exit code 0 or specific Nix evaluation output
    Expected Result: Module parses correctly
    Evidence: Nix output captured
  ```

  **Commit**: YES
  - Message: `docs(nix): add example NixOS service module`
  - Files: `nix/module.nix`

---

- [ ] 18. README Documentation

  **What to do**:
  - Create comprehensive README.md
  - Include: Overview, Installation, Usage, API Reference
  - Add examples for Docker, Nix, and direct Python usage
  - Document all endpoints with curl examples
  - Include troubleshooting section

  **Must NOT do**:
  - Do NOT duplicate API spec (reference it)

  **Recommended Agent Profile**:
  - **Category**: `writing`
    - Reason: Documentation writing
  - **Skills**: []

  **Parallelization**:
  - **Can Run In Parallel**: NO
  - **Parallel Group**: Sequential (last task)
  - **Blocks**: None
  - **Blocked By**: Tasks 16, 17

  **README Structure**:
  ```markdown
  # ZUGFeRD-Service

  ## Overview
  ## Quick Start
  ### Docker
  ### Nix
  ### Python (Development)
  ## API Reference
  ### GET /health
  ### POST /extract
  ### POST /validate
  ## Configuration
  ## NixOS Deployment
  ## Development
  ## Troubleshooting
  ## License
  ```

  **Acceptance Criteria**:

  **Agent-Executed QA Scenarios:**

  ```
  Scenario: README contains all required sections
    Tool: Bash
    Steps:
      1. grep -c "## " README.md
      2. Assert: At least 8 sections
      3. grep "curl" README.md | wc -l
      4. Assert: At least 3 curl examples
    Expected Result: Comprehensive documentation
    Evidence: grep output captured
  ```

  **Commit**: YES
  - Message: `docs: add comprehensive README with installation and usage guide`
  - Files: `README.md`

---

## Commit Strategy

| After Task | Message | Files | Verification |
|------------|---------|-------|--------------|
| 1 | `feat(project): initialize ZUGFeRD service` | pyproject.toml, src/, tests/ | toml parse |
| 2 | `test(fixtures): add ZUGFeRD sample PDFs` | tests/fixtures/ | file exists |
| 3 | `feat(models): add Pydantic models` | src/models.py | pytest |
| 4 | `feat(extractor): implement extraction` | src/extractor.py | pytest |
| 5 | `feat(pdf-parser): implement PDF parsing` | src/pdf_parser.py | pytest |
| 6 | `feat(utils): add utilities` | src/utils.py | pytest |
| 7 | `feat(validator): implement validation` | src/validator.py | pytest |
| 8-9 | `feat(api): add FastAPI app + health` | src/main.py | curl |
| 10 | `feat(api): add /extract endpoint` | src/main.py | pytest |
| 11 | `feat(api): add /validate endpoint` | src/main.py | pytest |
| 12 | `feat(api): add error handling` | src/main.py | curl |
| 13 | `test(integration): add e2e tests` | tests/ | pytest |
| 14 | `build(docker): add Dockerfile` | Dockerfile | docker build |
| 15 | `build(docker): add docker-compose` | docker-compose.yml | compose up |
| 16 | `build(nix): add flake.nix` | flake.nix | nix build |
| 17 | `docs(nix): add NixOS module` | nix/module.nix | nix eval |
| 18 | `docs: add README` | README.md | grep check |

---

## Success Criteria

### Verification Commands
```bash
# All tests pass
pytest tests/ -v
# Expected: All tests pass (exit code 0)

# Docker builds and runs
docker build -t zugferd-service .
docker run -p 5000:5000 zugferd-service &
curl http://localhost:5000/health
# Expected: {"status": "healthy", "version": "1.0.0"}

# Nix builds and runs
nix build .#zugferd-service
./result/bin/zugferd-service &
curl http://localhost:5000/health
# Expected: {"status": "healthy", "version": "1.0.0"}

# Extract endpoint works
PDF_BASE64=$(base64 -w 0 tests/fixtures/sample_en16931.pdf)
curl -X POST http://localhost:5000/extract \
  -H "Content-Type: application/json" \
  -d "{\"pdf_base64\": \"$PDF_BASE64\"}" | jq '.is_zugferd'
# Expected: true
```

### Final Checklist
- [ ] All 18 tasks completed
- [ ] All tests pass (pytest)
- [ ] Docker image builds (<500MB)
- [ ] Docker container runs and responds
- [ ] Nix flake builds without errors
- [ ] Nix package runs and responds
- [ ] All endpoints return expected responses
- [ ] README documents all features
- [ ] No "Must NOT Have" items present
