Structured reasoning framework for AI coding tools, quint-code enables auditable decision-making by creating evidence trails for AI-generated suggestions. It targets developers using AI assistants like Claude Code, Gemini CLI, Cursor, and Codex CLI, providing a rigorous process to understand and document the rationale behind AI-driven development choices, thereby mitigating hidden risks.

How It Works

Quint Code implements Anatoly Levenchuk's First Principles Framework (FPF), a methodology for rigorous, auditable reasoning. The core cycle involves Abduction to generate competing hypotheses, Deduction to verify logic and constraints, and Induction to gather empirical evidence through tests or research. This process transforms the "black box" nature of AI reasoning into a transparent, evidence-backed audit trail, documenting the rationale in a durable record.

Quick Start & Requirements

• Install: Use the provided binary script: curl -fsSL https://raw.githubusercontent.com/m0n0x41d/quint-code/main/install.sh | bash. Alternatively, build from source using Go.
• Prerequisites: Go compiler (for source build). Requires integration with supported AI coding tools (Claude Code, Cursor, Gemini CLI, Codex CLI).
• Initialize: Run quint-code init within your project directory. Use flags like --claude, --cursor, --gemini, --codex, or --all to configure for specific tools.
• Documentation: FPF Engine Details: docs/fpf-engine.md. Architecture: docs/fpf-engine.md.

Highlighted Details

• Implements the First Principles Framework (FPF) for structured, auditable reasoning.
• Supports multiple AI coding assistants, with specific configurations for Claude Code, Cursor, Gemini CLI, and Codex CLI.
• Provides commands for a full reasoning cycle: initialization (/q0-init), hypothesis generation (/q1-hypothesize), verification (/q2-verify), validation (/q3-validate), auditing (/q4-audit), and decision-making (/q5-decide).
• Includes features for managing knowledge base, checking for expired evidence (/q-decay), and reconciling with code changes (/q-actualize).

Maintenance & Community

No specific details regarding maintainers, community channels (e.g., Discord, Slack), or a public roadmap were found in the provided README.

Licensing & Compatibility

• License: MIT License.
• Compatibility: The MIT license is permissive and generally compatible with commercial use and closed-source projects.

Limitations & Caveats

The Codex CLI has a limitation where it does not support per-project MCP configuration, requiring quint-code init --codex to be run in each project directory to switch the active project configuration.