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ma-data-extraction

Extract and structure meta-analysis study data into a SQLite database.

115|45|Updated Feb 5, 2026
Search Tags:#provenance#sqlite#meta-analysis#data-extraction#data-dictionary#pdf-extraction#web-based
One-click install
npx skills add https://github.com/htlin222/meta-pipe --skill ma-data-extraction
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ma-data-extraction
Source: https://github.com/htlin222/meta-pipe/tree/main/ma-data-extraction
Command: npx skills add https://github.com/htlin222/meta-pipe --skill ma-data-extraction

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, pdfplumber, pypdf, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Defines extraction schema, extracts study data from full texts, and stores it in a structured database to support reproducible meta-analyses.

Core Features & Use Cases

  • Web-first hybrid extraction workflow that populates an extraction SQLite database for scalable meta-analysis data.
  • PDF-based extraction for gaps using an LLM-assisted approach to improve completeness.
  • Data dictionary creation, provenance tracking, and optional source validation to ensure traceability.

Quick Start

Run the end-to-end extraction workflow to initialize the database, populate the extraction tables, and validate sources.

Frequently Asked Questions about ma-data-extraction

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

FAQPage Schema
How do I extract structured data from full texts for a meta-analysis?▼

To extract structured data for a meta-analysis, use a web-first pipeline with a dictionary-driven schema to populate an extraction database, ensuring traceable and reproducible study data from full texts.

Can I use LLM-assisted PDF extraction to fill gaps in web-based data extraction?▼

Yes, you can use LLM-assisted PDF extraction to fill gaps in web-based data extraction. This hybrid approach improves completeness by verifying full texts when web extraction leaves missing fields.

What is a data dictionary and provenance tracking in meta-analysis data extraction?▼

A data dictionary defines the extraction schema fields, while provenance tracking records the origin of each extracted data point, ensuring traceability and source validation for reproducible meta-analyses.

How do I initialize a SQLite database for storing extracted meta-analysis data?▼

You initialize a SQLite database for extracted meta-analysis data by running the provided scripts alongside a data-dictionary markdown and manifest to create and populate the extraction tables.

Does the extraction pipeline work with pdfplumber and pypdf for source validation?▼

Yes, the extraction pipeline works with pdfplumber and pypdf for source validation. These dependencies enable text parsing to verify full-text sources and fill extraction gaps.

What is the best way to structure study data from full texts into a SQLite database?▼

The best way to structure study data into a SQLite database is using a dictionary-driven workflow that initializes tables, runs web extraction, and validates sources to support scalable meta-analyses.

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