Preflight

About

Preflight addresses common inefficiencies in AI coding, particularly with Claude Code, by acting as a comprehensive pre-check system. After analyzing extensive real-world usage data, it was found that vague prompts lead to significant token waste and iterative correction cycles. Preflight mitigates these issues with an 18-tool Model Context Protocol (MCP) server that enforces prompt discipline, provides semantic search across months of past coding sessions via LanceDB, and verifies code before completion, drastically reducing wasted tokens and improving development workflow.

Key Features

• Provides semantic search across months of Claude Code session history using LanceDB vector embeddings
• Monitors session health, tracks corrections, and generates handoff briefs for new sessions
• Enforces prompt discipline with 12 specialized tools to prevent ambiguous AI instructions
• Automates code verification, including type checks, tests, and build processes, before declaring tasks complete
• 0 GitHub stars
• Supports local (Xenova) or OpenAI-powered embeddings for efficient history indexing

Use Cases

• Preventing costly wrong-fix cycles and token waste caused by vague AI coding prompts
• Quickly retrieving past coding solutions or context through semantic search across historical sessions
• Ensuring code quality and readiness by automatically running checks before task completion