This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content
What I Built
I built an automated, AI-driven Transport & Fleet Safety Operations Manual backed by Sanity Studio and queried in real-time through an editor assistant.
Sanity Project Details
- Project ID / Dataset: dyxta77n
How I Used Sanity
My agent reads and queries structured compliance data stored in Sanity Studio.
- The Setup: I configured a custom schema to model multi-category safety records.
- The Knowledge Base: I populated the dataset with six core operational documents covering Pre-Trip Inspections, Emergency Spill/Hazmat Protocols, Severe Weather Guidelines, Post-Accident Procedures, Hours of Service (HOS) & Fatigue Management, and Cargo Securement Standards.
- The Agent Workflow: Using a local Model Context Protocol (MCP) bridge, my VS Code AI assistant directly connects to Sanity datasets, allowing it to perform complex, multi-document synthesis and cross-reference penalties, operational timelines, and safety criteria on the fly.
Code & Architecture
- Stack: Sanity Studio (
complianceDocument.ts), local MCP server, and VS Code AI assistant - Dataset: Project
dyxta77n - GitHub Repository: View Source Code on GitHub
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