Agent skill · research science · datadrivenconstruction
document-classification-nlp
Automatically classify and extract information from construction documents using NLP. Categorize RFIs, submittals, change orders, specifications, and contracts.
Why this skill is useful
Provides domain-specific NLP techniques and classification patterns for construction documents that the AI wouldn't reliably generate on its own.
What it needs
Requires python3 installed locally. About 5k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
Document Classification with NLP Overview This skill implements NLP-based document classification and information extraction for construction projects. Automate document sorting, key term extraction, and content analysis. Document Types: RFIs (Requests for Information) Submittals and shop drawings Change orders and variations Specifications and standards Contracts and agreements Safety reports and permits Quick Start Advanced Classification System Document Classifier Class Information Extraction Key Information Extractor Processing Pipeline Quick Reference Document Type Key Patterns Extracted Info -------------- -------------- ---------------- RFI "request for information", "clarify" Number, spec section, question Submittal "shop drawing", "approval request" Number, product, spec section Change Order "change order", "additional cost" Number, cost, duration impact Specification "Section XX XX XX" Section number, requirements Safety Report "incident", "hazard" Date, type, severity Resources spaCy: https://spacy.io Scikit-learn: https://scikit-learn.org DDC Website: https://datadrivenconstruction.io Next Steps See vector-search for semantic document search See llm-data-automation for advanced extraction See pdf-to-structured for PDF processing
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/document-classification-nlp