Caveman vs Aming Claw

Caveman is an open-source developer tool designed around a simple yet powerful premise: "why use many token when few do trick." Built by maker Julius Brussee, Caveman allows developers to wrap AI coding assistants and LLM workflows—such as Claude Code, Codex, and Hermes—with a single command.

At its core, Caveman operates as a local proxy that intelligently compresses logs, tool outputs, and source code files before sending them to LLM provider endpoints. In a pinned 54-run benchmark, Caveman reduced input tokens by 33.2% while achieving 18/18 correctness checks, ensuring token savings do not compromise code or task accuracy.

In addition to compressing standard logs and file outputs, Caveman can execute existing agent skills with approximately 70% fewer tokens by rendering and loading text as images. Backed by a thriving open-source ecosystem with over 97,000 GitHub stars, Caveman provides a practical, efficient solution for optimizing developer workflows and reducing API usage costs.

Aming Claw is an innovative open-source governance infrastructure designed specifically to tackle the common problem of AI agent drift during long-running tasks. As agents execute extended workflows, they frequently lose their verified state and begin guessing their next actions, leading to errors and inefficiency. This tool steps in to verify an agent's exact position, enforce a single legal next step, and maintain robust causal evidence across different task handoffs. By integrating a graph-backed backlog, independent worker and QA roles, auditable bypasses, and controlled merge or reconcile flows, Aming Claw transforms how developers manage autonomous systems. Instead of humans constantly stepping in as an expensive GPS to correct course, the infrastructure handles oversight so that human intervention is reserved purely for critical high-level judgment.