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terry90918
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jurislm-shared-sync

Automate full synchronization of jurislm_shared_db with judicial, law, and taxonomy data.

Updated Aug 23, 2026
Search Tags:#postgresql#data pipeline#taxonomy#pgvector#database sync#judicial data#legal statutes
One-click install
npx skills add https://github.com/terry90918/jurislm-plugins --skill jurislm-shared-sync
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: jurislm-shared-sync
Source: https://github.com/terry90918/jurislm-plugins/tree/main/plugins/jurislm-dev/skills/jurislm-shared-sync
Command: npx skills add https://github.com/terry90918/jurislm-plugins --skill jurislm-shared-sync

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex and time-consuming process of synchronizing the jurislm_shared_db with up-to-date judicial, law, and taxonomy data, ensuring the AI has access to the latest legal information.

Core Features & Use Cases

  • Full Database Synchronization: Orchestrates a multi-stage pipeline to ingest and update judicial decisions (051-054), legal statutes, and legal synonyms.
  • Automated Workflow: Handles database migrations, data parsing, embedding generation, and data import with minimal user intervention.
  • Use Case: When new court rulings are published, this Skill can be triggered to automatically download, process, and add them to the shared database, making them immediately available for AI analysis.

Quick Start

Run the full synchronization workflow for the shared database.

Frequently Asked Questions about jurislm-shared-sync

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

FAQPage Schema
How do I automate syncing a PostgreSQL legal database with new court rulings and statutes?▼

Automating legal database sync requires orchestrating a multi-stage pipeline for data parsing, embedding generation, and import. This Skill handles that workflow end-to-end, updating judicial decisions, legal statutes, and taxonomy data with minimal manual intervention.

What is the process for importing judicial data and generating embeddings for AI consumption?▼

Generating embeddings for AI consumption involves parsing legal sources, running database migrations, and importing the structured judicial data. This Skill automates that exact sequence to ensure the shared legal database contains up-to-date, AI-ready information.

Can I use pgvector to store embeddings when syncing legal statutes and taxonomy data?▼

Yes, pgvector is supported for embedding storage during the legal data synchronization pipeline. The workflow generates embeddings from parsed judicial decisions and legal statutes, then imports them into the PostgreSQL database for AI analysis.

Do I need to manually run database migrations before importing judicial decisions?▼

No, manual database migrations are not required before importing judicial decisions. The synchronization pipeline automates the full process, handling migrations, data parsing, and embedding generation sequentially before the final data import.

What's the best way to keep a shared legal database updated with the latest legal information?▼

Keeping a shared legal database updated requires triggering a full synchronization workflow that downloads and processes new legal sources. This Skill orchestrates that entire pipeline, making new court rulings and statutes immediately available for AI queries.

Why does my legal data pipeline fail to generate embeddings during taxonomy import?▼

Embedding generation failures during taxonomy import often stem from skipped database migrations or incomplete data parsing. This Skill prevents such issues by orchestrating the full pipeline sequentially, ensuring each stage completes before the next begins.

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