Log compression 2

AI token optimization stack for reducing agent costs and context Caveman is an AI efficiency operating stack that reduces the cost and context size of agent-native development. It provides an MIT-licensed skill, a free local proxy, an Agent SDK, and planned cloud and enterprise services. Caveman compresses logs, JSON, code, diffs, tables, tool outputs, and files before provider calls while preserving recoverable original bytes. It also supports caching, eval-gated model routing, token usage visibility, savings estimates, and verification workflows. The local wrap works with users' own provider keys and does not require a Caveman account.

Local CLI that reduces coding-agent token waste JFrog Boost is a free, local-first command-line tool that compresses noisy terminal output, MCP responses, file contents, and other tool data before it reaches coding agents such as Cursor, Claude Code, Codex, GitHub Copilot, and OpenCode. It reduces token usage while preserving important information such as errors, failures, summaries, and relevant context. Boost uses reversible compression and retrieval, allowing agents or developers to restore the original output when needed. It also provides graph-based code retrieval, file optimization, observability, telemetry, and enterprise-focused privacy.