tabular-review

Extract evidence-backed spreadsheet rows from batch documents with typed columns and source citations.

Updated Dec 4, 2025
One-click install
npx skills add https://github.com/PolliticalSolutions/political-portal --skill tabular-review-polliticalsolutions
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tabular-review
Source: https://github.com/PolliticalSolutions/political-portal/tree/main/.claude/skills/corporate-legal/tabular-review
Command: npx skills add https://github.com/PolliticalSolutions/political-portal --skill tabular-review-polliticalsolutions

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually reviewing hundreds of similar documents and extracting the same fields into a spreadsheet is slow and inconsistent, especially when you must preserve traceable evidence for every cell.

Core Features & Use Cases

  • Spreadsheet-ready tabular extraction: Produces one row per document and one column per requested data point.
  • Typed columns with evidence: Supports multiple column types (including verbatim and classification) and requires each cell to be backed by the exact quoted source text and location.
  • Verification-focused workflow: Uses explicit states (not_present, unclear, needs_review) to drive human follow-up and prevent silent omissions.
  • Batch diligence use cases: Built for M&A-style diligence, but applicable to any bulk review such as vendor contract audits or contract portfolio comparisons.

Quick Start

Run a tabular review for the contracts in the specified folder and output an evidence-backed spreadsheet with quotes and locations for every extracted cell.

Frequently Asked Questions about tabular-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract data from multiple contracts into a spreadsheet with evidence quotes?▼

Tabular review extracts standardized data points from multiple contracts into a spreadsheet grid, backing every cell with verbatim source quotes and location citations. It maps each row to one document and each column to a specific field for batch diligence.

What is the best way to handle bulk document review for M&A diligence?▼

Bulk document review for M&A diligence is handled by mapping each document to a row and each requested data point to a typed column. This schema-driven extraction enforces verbatim quoting and explicit states like not_present or needs_review to prevent silent omissions.

How does schema-driven extraction handle missing or unclear contract terms?▼

Schema-driven extraction handles missing or unclear contract terms by assigning explicit states such as not_present, unclear, or needs_review. This verification-focused workflow drives human follow-up instead of silently leaving cells blank during batch contract reviews.

Can I use tabular extraction for vendor contract audits and portfolio comparisons?▼

Tabular extraction works for vendor contract audits and portfolio comparisons by generating a standardized grid where each row represents a document. It requires every extracted data point to include the exact quoted source text and its location reference for traceability.

Does contract diligence extraction require specific file formats or dependencies?▼

Contract diligence extraction requires no specific dependencies and processes documents from a specified folder to output an evidence-backed spreadsheet. It applies typed schema constraints to ensure consistent data extraction across various batch document review scenarios.