What happens if a specific data point is missing in a document?

If an agent cannot find information for a requested column, it marks the value as 'Not found' and provides an explanation in the citation field.

Can this skill process both PDF and Word files simultaneously?

Yes, the skill is designed to handle both .pdf and .docx formats within the same folder and process them together into one output.

Can I define my own columns for the extraction?

Absolutely. During the setup phase, you can define specific labels like 'Effective Date', 'Governing Law', or 'Liability Cap' to tailor the review to your needs.

Is there a limit to how many documents can be reviewed?

The skill uses parallel agents (up to 10 by default) to handle large volumes. Performance depends on your system resources and the number of documents.

How does the skill handle citations for the extracted information?

Every cell in the generated Excel sheet includes a comment with a contextual quote and a hyperlink that points directly to the specific page or section in the source document.

Tabular Document Review

Name: Tabular Document Review
Author: lawvable

bylawvable

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Productivity & Workflow

Automates the extraction of structured data from multiple PDF and Word documents into a comprehensive Excel matrix with source citations.

About

The Tabular Review skill enables Claude to perform high-volume document analysis by scanning directories for PDF and DOCX files, extracting user-defined data points, and compiling them into a structured Excel workbook. It leverages parallel background agents to process documents concurrently, ensuring speed even with large datasets. Each entry in the resulting Excel file includes precise citations, contextual quotes, and hyperlinks directly to specific document pages, making it an essential tool for legal contract review, due diligence, and comparative document analysis.

Key Features

Contextual source quotes for easy verification of extracted data
38 GitHub stars
User-defined extraction columns for customized document matrices
Multi-format support for PDF and DOCX file extraction
Parallel document processing via concurrent background agents
Automated Excel workbook generation with hyperlinked citations

Use Cases

Comparing specific clauses or provisions across dozens of legal contracts
Creating a structured data matrix from a large directory of research papers or reports
Extracting key dates, parties, and financial terms for due diligence reports

About

Key Features

Contextual source quotes for easy verification of extracted data
38 GitHub stars
User-defined extraction columns for customized document matrices
Multi-format support for PDF and DOCX file extraction
Parallel document processing via concurrent background agents
Automated Excel workbook generation with hyperlinked citations

Use Cases

Comparing specific clauses or provisions across dozens of legal contracts
Creating a structured data matrix from a large directory of research papers or reports
Extracting key dates, parties, and financial terms for due diligence reports