菜单
Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Segment a SKU portfolio on value (ABC) and demand variability (XYZ), produce the 9-box with a planning policy per cell, and reallocate planner attention accordingly. Use when the user mentions ABC analysis, inventory segmentation, SKU rationalization, stok segmentasyonu, envanter sınıflandırma, or asks which items deserve forecasting effort. Differentiator - ABC alone is treated as half an answer; policy lives in the value x variability combination.
Evaluate demand-forecast quality honestly - WMAPE, bias and Forecast Value Added against a naive benchmark over a rolling-origin backtest. Use when the user mentions forecast accuracy, MAPE, demand planning performance, tahmin doğruluğu, talep tahmini, or asks whether a forecasting process or tool is worth it. Differentiator - judges the process (value added vs doing nothing), not just the model.
Audit delivery performance from order-level data - compute the OTIF metric ladder (tolerant to strict), find where lateness concentrates, and quantify the gap between the reported KPI and what customers experience. Use when the user mentions OTIF, on-time delivery, delivery performance, late orders, teslimat performansı, zamanında teslimat, or asks why customers complain despite a high on-time score. Differentiator - exposes measurement choices before optimizing operations.
Build a decision-grade Pareto for downtime, defects, complaints or delays - with unit-of-measure discipline, category hygiene, exposure normalization and a follow-up metric. Use when the user mentions pareto analysis, kök neden, duruş analizi, downtime, arıza analizi, defect ranking, şikayet analizi, 80/20 analysis. Differentiator - treats the Pareto as the start of a causal investigation, not a bar chart deliverable.
Size or audit safety stock with assumption checks - the z*sigma*sqrt(LT) formula plus an empirical stress test of what it actually delivers (cycle service vs fill rate) per variability class. Use when the user mentions safety stock, emniyet stoku, emniyet stoğu, reorder point, service level, stok seviyesi belirleme. Differentiator - refuses to hand back a number without validating the demand-distribution assumptions behind it.
Turn raw operational data into a weekly management report that answers exactly three questions - what changed, where is it concentrated, what needs a decision. Use when the user mentions weekly report, haftalık rapor, yönetim raporu, ops review, KPI summary, or asks to summarize operational data for managers. Differentiator - contract-first reporting with plain-language findings and driver decomposition, never a chart dump.
| name | PDF Processing Pro |
| description | Production-ready PDF processing with forms, tables, OCR, validation, and batch operations. Use when working with complex PDF workflows in production environments, processing large volumes of PDFs, or requiring robust error handling and validation. |
Production-ready PDF processing toolkit with pre-built scripts, comprehensive error handling, and support for complex workflows.
import pdfplumber
with pdfplumber.open("document.pdf") as pdf:
text = pdf.pages[0].extract_text()
print(text)
python scripts/analyze_form.py input.pdf --output fields.json
# Returns: JSON with all form fields, types, and positions
python scripts/fill_form.py input.pdf data.json output.pdf
# Validates all fields before filling, includes error reporting
python scripts/extract_tables.py report.pdf --output tables.csv
# Extracts all tables with automatic column detection
All scripts include:
--help flag for all scriptsFor complete form workflows including:
See FORMS.md
For complex table extraction:
See TABLES.md
For scanned PDFs and image-based documents:
See OCR.md
analyze_form.py - Extract form field information
python scripts/analyze_form.py input.pdf [--output fields.json] [--verbose]
fill_form.py - Fill PDF forms with data
python scripts/fill_form.py input.pdf data.json output.pdf [--validate]
validate_form.py - Validate form data before filling
python scripts/validate_form.py data.json schema.json
extract_tables.py - Extract tables to CSV/Excel
python scripts/extract_tables.py input.pdf [--output tables.csv] [--format csv|excel]
extract_text.py - Extract text with formatting preservation
python scripts/extract_text.py input.pdf [--output text.txt] [--preserve-formatting]
merge_pdfs.py - Merge multiple PDFs
python scripts/merge_pdfs.py file1.pdf file2.pdf file3.pdf --output merged.pdf
split_pdf.py - Split PDF into individual pages
python scripts/split_pdf.py input.pdf --output-dir pages/
validate_pdf.py - Validate PDF integrity
python scripts/validate_pdf.py input.pdf
# 1. Analyze form structure
python scripts/analyze_form.py template.pdf --output schema.json
# 2. Validate submission data
python scripts/validate_form.py submission.json schema.json
# 3. Fill form
python scripts/fill_form.py template.pdf submission.json completed.pdf
# 4. Validate output
python scripts/validate_pdf.py completed.pdf
# 1. Extract tables
python scripts/extract_tables.py monthly_report.pdf --output data.csv
# 2. Extract text for analysis
python scripts/extract_text.py monthly_report.pdf --output report.txt
import glob
from pathlib import Path
import subprocess
# Process all PDFs in directory
for pdf_file in glob.glob("invoices/*.pdf"):
output_file = Path("processed") / Path(pdf_file).name
result = subprocess.run([
"python", "scripts/extract_text.py",
pdf_file,
"--output", str(output_file)
], capture_output=True)
if result.returncode == 0:
print(f"✓ Processed: {pdf_file}")
else:
print(f"✗ Failed: {pdf_file} - {result.stderr}")
All scripts follow consistent error patterns:
# Exit codes
# 0 - Success
# 1 - File not found
# 2 - Invalid input
# 3 - Processing error
# 4 - Validation error
# Example usage in automation
result = subprocess.run(["python", "scripts/fill_form.py", ...])
if result.returncode == 0:
print("Success")
elif result.returncode == 4:
print("Validation failed - check input data")
else:
print(f"Error occurred: {result.returncode}")
All scripts require:
pip install pdfplumber pypdf pillow pytesseract pandas
Optional for OCR:
# Install tesseract-ocr system package
# macOS: brew install tesseract
# Ubuntu: apt-get install tesseract-ocr
# Windows: Download from GitHub releases
--parallel flag (where supported)"Module not found" errors:
pip install -r requirements.txt
Tesseract not found:
# Install tesseract system package (see Dependencies)
Memory errors with large PDFs:
# Process page by page instead of loading entire PDF
with pdfplumber.open("large.pdf") as pdf:
for page in pdf.pages:
text = page.extract_text()
# Process page immediately
Permission errors:
chmod +x scripts/*.py
All scripts support --help:
python scripts/analyze_form.py --help
python scripts/extract_tables.py --help
For detailed documentation on specific topics, see: