MartinLoop

MartinLoop is an open-source governance layer for AI coding agents. If your team relies on agents like Claude, Codex, or Cursor to write code, you've probably noticed the same problem: agents can loop forever, burning tokens and budget without finishing. MartinLoop gives those agents a finish line. It sits between your agent and the model provider, enforcing spending limits, classifying failures, and ensuring every run either completes or stops cleanly. The result is a controlled runtime — not an uncontrolled loop.

The tool works as a CLI (npm install -g martin-loop) and includes a dashboard with real-time telemetry. Before each run, you set a dollar budget. MartinLoop tracks every token cost, including ones older tools miss, and stops before the cap hits. When something fails, it doesn't just retry blindly. It diagnoses the type of failure — syntax error, hallucination, logic bug — and applies the right fix. Each attempt gets sharper. The dashboard shows exactly where your money went, what failed, and what got saved. Five things happen on every run: learn from attempts, fix the right thing, hold the spending limit, stop when done, and log every cost.

MartinLoop is built for teams that are shipping AI code and need tighter controls over cost and quality. Engineering leads can set budgets and let agents work overnight, then review a clean report in the morning. Finance gets a shared source of truth — cost per task, savings per month, ROI per agent. The tool is Apache 2.0 licensed, free to start, and works with any model (Claude, GPT, Gemini, open-source). For larger teams, MartinLoop360 adds business context (CRM, financial rules, approval gates) and HeadlessOS handles enterprise orchestration with job queues and compliance-ready audit trails. If you're tired of explaining runaway AI bills, MartinLoop gives you the numbers to turn budget reviews into expansion conversations.