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Get Started Free →PDF processing for construction documents: RFIs, submittals, specifications, drawing packages. Extract data, merge packages, fill forms.
.claude/skills/datadrivenconstruction-pdf-construction/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 11% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 22% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 45% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 164% | 0% |
| case-15 | ✗→✓ | ▲ Improved | -18% | 0% |
Adapted from Anthropic's PDF skill for construction document workflows.
Extract structured data from Request for Information documents.
pythonfrom pypdf import PdfReader import re def extract_rfi_data(pdf_path: str) -> dict: """Extract RFI fields from PDF.""" reader = PdfReader(pdf_path) text = "" for page in reader.pages: text += page.extract_text() # Parse common RFI fields rfi_data = { 'rfi_number': re.search(r'RFI\s*#?\s*(\d+)', text), 'subject': re.search(r'Subject:?\s*(.+?)(?:\n|$)', text), 'from': re.search(r'From:?\s*(.+?)(?:\n|$)', text), 'to': re.search(r'To:?\s*(.+?)(?:\n|$)', text), 'date': re.search(r'Date:?\s*(\d{1,2}[/-]\d{1,2}[/-]\d{2,4})', text), 'spec_section': re.search(r'Spec(?:ification)?\s*Section:?\s*(.+?)(?:\n|$)', text), 'drawing_ref': re.search(r'Drawing\s*(?:Ref)?:?\s*(.+?)(?:\n|$)', text), } return {k: v.group(1) if v else None for k, v in rfi_data.items()}
Merge multiple PDFs into organized submittal packages.
pythonfrom pypdf import PdfWriter, PdfReader from pathlib import Path def create_submittal_package( cover_sheet: str, product_data: list, shop_drawings: list, output_path: str ) -> str: """Create organized submittal package.""" writer = PdfWriter() # Add cover sheet writer.append(cover_sheet) # Add bookmarked sections page_num = len(PdfReader(cover_sheet).pages) # Product Data section writer.add_outline_item("Product Data", page_num) for pdf in product_data: writer.append(pdf) page_num += len(PdfReader(pdf).pages) # Shop Drawings section writer.add_outline_item("Shop Drawings", page_num) for pdf in shop_drawings: writer.append(pdf) page_num += len(PdfReader(pdf).pages) with open(output_path, "wb") as output: writer.write(output) return output_path
Extract specification sections for analysis.
pythonimport pdfplumber def extract_spec_sections(pdf_path: str) -> dict: """Extract specification sections by division.""" sections = {} with pdfplumber.open(pdf_path) as pdf: current_section = None current_text = [] for page in pdf.pages: text = page.extract_text() # Match CSI MasterFormat sections for line in text.split('\n'): # Match section headers like "03 30 00 - Cast-in-Place Concrete" match = re.match(r'^(\d{2}\s?\d{2}\s?\d{2})\s*[-–]\s*(.+)$', line) if match: if current_section: sections[current_section] = '\n'.join(current_text) current_section = match.group(1).replace(' ', '') current_text = [match.group(2)] elif current_section: current_text.append(line) if current_section: sections[current_section] = '\n'.join(current_text) return sections
Split drawing packages by sheet.
pythondef split_drawing_package(pdf_path: str, output_dir: str) -> list: """Split drawing package into individual sheets.""" reader = PdfReader(pdf_path) output_dir = Path(output_dir) output_dir.mkdir(exist_ok=True) sheets = [] for i, page in enumerate(reader.pages): # Extract sheet number from page (if text-based) text = page.extract_text() sheet_match = re.search(r'([A-Z]+[-]?\d+)', text[:500]) sheet_name = sheet_match.group(1) if sheet_match else f"Page_{i+1:03d}" writer = PdfWriter() writer.add_page(page) output_file = output_dir / f"{sheet_name}.pdf" with open(output_file, "wb") as f: writer.write(f) sheets.append(str(output_file)) return sheets
python# Example: Process RFI and add to tracking spreadsheet import pandas as pd # Extract RFI data rfi_data = extract_rfi_data("RFI_045.pdf") # Load existing tracker tracker = pd.read_excel("RFI_Log.xlsx") # Add new entry new_row = pd.DataFrame([rfi_data]) tracker = pd.concat([tracker, new_row], ignore_index=True) # Save updated tracker tracker.to_excel("RFI_Log.xlsx", index=False)
bashpip install pypdf pdfplumber reportlab
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 15,385 | 15,879 | +3% | 1 | 1 | 0% | 3,167 | 3,531 | +11% | 0 | 0 | — |
case-02 | fail→fail | 14,115 | 12,754 | -10% | 1 | 1 | 0% | 2,791 | 4,160 | +49% | 0 | 0 | — |
case-03 | fail→pass | 20,005 | 17,227 | -14% | 1 | 1 | 0% | 3,843 | 4,686 | +22% | 0 | 0 | — |
case-04 | fail→fail | 14,146 | 14,580 | +3% | 1 | 1 | 0% | 2,741 | 4,528 | +65% | 0 | 0 | — |
case-05 | pass→pass | 11,500 | 5,335 | -54% | 1 | 1 | 0% | 2,158 | 2,492 | +15% | 0 | 0 | — |
case-06 | fail→fail | 16,933 | 12,466 | -26% | 1 | 1 | 0% | 3,171 | 3,946 | +24% | 0 | 0 | — |
case-07 | fail→fail | 12,825 | 8,040 | -37% | 1 | 1 | 0% | 2,303 | 2,958 | +28% | 0 | 0 | — |
case-08 | fail→pass | 12,708 | 6,969 | -45% | 1 | 1 | 0% | 1,935 | 2,811 | +45% | 0 | 0 | — |
case-09 | fail→fail | 14,948 | 12,218 | -18% | 1 | 1 | 0% | 2,414 | 3,403 | +41% | 0 | 0 | — |
case-10 | fail→pass | 22,821 | 9,020 | -60% | 1 | 1 | 0% | 1,162 | 3,070 | +164% | 0 | 0 | — |
case-11 | pass→pass | 11,662 | 6,658 | -43% | 1 | 1 | 0% | 2,057 | 2,604 | +27% | 0 | 0 | — |
case-12 | pass→pass | 9,717 | 5,370 | -45% | 1 | 1 | 0% | 1,755 | 2,452 | +40% | 0 | 0 | — |
case-13 | fail→fail | 7,833 | 6,982 | -11% | 1 | 1 | 0% | 1,390 | 2,745 | +97% | 0 | 0 | — |
case-14 | fail→fail | 14,295 | 7,064 | -51% | 1 | 1 | 0% | 2,696 | 2,763 | +2% | 0 | 0 | — |
case-15 | fail→pass | 15,969 | 4,313 | -73% | 1 | 1 | 0% | 2,649 | 2,181 | -18% | 0 | 0 | — |
case-16 | fail→pass | 17,723 | 10,629 | -40% | 1 | 1 | 0% | 3,364 | 3,443 | +2% | 0 | 0 | — |
case-17 | pass→pass | 12,983 | 33,953 | +162% | 1 | 1 | 0% | 2,098 | 1,895 | -10% | 0 | 0 | — |
case-18 | pass→pass | 11,987 | 8,394 | -30% | 1 | 1 | 0% | 2,119 | 3,015 | +42% | 0 | 0 | — |
case-19 | fail→pass | 15,041 | 4,945 | -67% | 1 | 1 | 0% | 2,685 | 2,315 | -14% | 0 | 0 | — |
case-20 | pass→pass | 11,902 | 11,783 | -1% | 1 | 1 | 0% | 2,237 | 3,603 | +61% | 0 | 0 | — |
case-21 | fail→fail | 19,322 | 18,440 | -5% | 1 | 1 | 0% | 3,526 | 4,840 | +37% | 0 | 0 | — |
case-22 | pass→pass | 14,495 | 12,118 | -16% | 1 | 1 | 0% | 2,548 | 3,692 | +45% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 21 counted toward the lift figure. The other 1 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +32 percentage points is the difference between those two pass rates over the 21 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.