01-document-processing/document-structure-analysis/SKILL.md

---
name: document-structure-analysis
description: Map Nordea PDF layout into zones (header, account info, table,
  footer) and compute a layout signature hash for template matching. Use after
  text conversion to classify document regions and detect template version.
metadata:
  category: document_processing
  priority: CRITICAL
  config_id: document_structure_analysis
---

# Document Structure Analysis

## Purpose
Zone classification + template fingerprinting. Enables template_library
matching (PerfectPDF Skill B) and anchors table extraction coordinates.

## Zones (Nordea Tiliote, A4 595x842)
| Zone | Y range | Contents |
|------|---------|----------|
| header | 15-126 | Nordea logo, bank info |
| account | 40-110 | Account holder, address, IBAN |
| period | ~130-160 | "Kausi: DD.MM.YYYY - DD.MM.YYYY" |
| table | 170-800 | Transaction rows |
| footer | 800-820 | "Sivu X/Y", disclaimers |

## Workflow
1. Load spans from `pdf-text-conversion`
2. Assign each span to a zone by bbox Y
3. Extract anchors: IBAN regex, "Kausi:" period line, "Sivu X/Y" page marker
4. Compute layout signature: SHA1 of (page_count, block_count per page,
   font set, zone boundaries)
5. Match signature against `templates` table -> template_id + version

## Code
```python
import hashlib, re

IBAN_RE = re.compile(r"FI\d{2}\s?\d{4}\s?\d{4}\s?\d{4}\s?\d{2}")
PERIOD_RE = re.compile(r"Kausi:\s*(\d{2}\.\d{2}\.\d{4})\s*-\s*(\d{2}\.\d{2}\.\d{4})")

def layout_signature(pages: list[dict]) -> str:
    parts = [str(len(pages))]
    for p in pages:
        fonts = sorted({s["font"] for s in p["spans"]})
        parts.append(f"{len(p['spans'])}:{'|'.join(fonts)}")
    return hashlib.sha1(";;".join(parts).encode()).hexdigest()

def find_anchors(full_text: str) -> dict:
    return {
        "iban": (m.group(0) if (m := IBAN_RE.search(full_text)) else None),
        "period": PERIOD_RE.findall(full_text),
    }
```

## Integration
- Feeds: `pdf-table-extraction` (zone coords), template matching
- Uses: `pdf-text-conversion` output

## Errors & Edge Cases
- Unknown signature -> create new template candidate, flag for human review
- Extra pages (attachments) -> exclude from signature, process separately