alansyahmi/Schemap

<div align="center"> <img src="docs/assets/Text_Logo__Dark_-removebg-preview2.png" alt="Schemap Logo — AI Database Context Compiler" width="340" /> <br/> <br/> <h1>Stop AI Agents From Guessing Your Database.</h1> <p><strong>The Deterministic AI Database Context Compiler for Claude Code, Cursor, Windsurf, Codex, and Copilot.</strong></p> <p> <a href="https://pypi.org/project/schemap-tool/"><img src="https://img.shields.io/pypi/v/schemap-tool.svg?color=blue" alt="PyPI Version"></a> <a href="https://pypi.org/project/schemap-tool/"><img src="https://img.shields.io/pypi/pyversions/schemap-tool.svg" alt="Python Versions"></a> <a href="https://github.com/alansyahmi/Schemap/blob/main/LICENSE"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT"></a> <img src="https://img.shields.io/badge/Claude%20Code-Supported-6366f1?logo=anthropic" alt="Claude Code"> <img src="https://img.shields.io/badge/Cursor-Rules%20Ready-000000" alt="Cursor"> <img src="https://img.shields.io/badge/Privacy-100%25%20Local--First-10b981" alt="Local First"> </p> </div>

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⚡ The Problem: Why AI Coding Agents Fail at SQL

Modern AI coding agents (Claude Code, Cursor, GitHub Copilot, Codex) struggle with production databases:

• Raw pg_dump SQL dumps waste 10,000+ tokens of precious context window.
• Cluttered DDL dumps introduce noisy system metadata and lock definitions.
• LLMs hallucinate non-existent foreign keys (e.g. guessing orders.customer_id when the column is orders.user_id), creating broken multi-table JOINs.

Schemap solves this. Schemap is a high-speed CLI compiler that introspects your database, computes an AI Readiness Score, and outputs clean, token-optimized context maps (schemap_database_context.md, CLAUDE.md, AGENTS.md).

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📊 Benchmarks: Next-Gen AI Models & Multi-Turn Agent Economics

*Measured using OpenAI tiktoken (cl100k_base / o200k_base across Claude Opus 5, GPT-5.6 Terr