A developer built and open-sourced optimAIzr, a fully local tool that analyzes Claude Code and Codex sessions to surface wasted token spend, such as oversized context, model mismatches, and error loops. The author analyzed ~1.25B tokens of their own sessions and found ~15% potentially optimizable. The tool has reached 2k+ npm downloads and now offers live recommendations inside Claude Code, with a hosted dashboard planned.
optimAIzr is an open-source AI usage optimizer for Claude Code and Codex. It analyzes logs to find cost wasted on re-reading existing context and warns in real time when a prompt cache is about to expire. It targets developers running long AI coding sessions who pay API prices for redundant context re-reads.
optimAIzr is an open-source AI usage optimizer for Claude Code and Codex. It analyzes logs to find cost wasted on re-reading existing context and warns in real time when a prompt cache is about to expire. It targets developers running long AI coding sessions who pay API prices for redundant context re-reads.
claude-finops is an npx-runnable CLI that reads Claude Code's local session transcripts (token counts, models, timestamps, tool calls) and computes what each session cost. It builds a local SQLite warehouse and serves a dashboard showing spend per project, waste detection, model-switch savings, and budget forecasts, entirely on-machine.
claude-finops is an npx-runnable CLI that reads Claude Code's local session transcripts (token counts, models, timestamps, tool calls) and computes what each session cost. It builds a local SQLite warehouse and serves a dashboard showing spend per project, waste detection, model-switch savings, and budget forecasts, entirely on-machine.
optimAIzr is a CLI tool that analyzes a developer's AI usage, identifies wasted tokens, and recommends ways to save tokens and money. It runs entirely locally, so usage data never leaves the machine. It targets developers spending on LLM APIs who want to reduce costs. Planned features include live recommendations.
optimAIzr is a CLI tool that analyzes a developer's AI usage, identifies wasted tokens, and recommends ways to save tokens and money. It runs entirely locally, so usage data never leaves the machine. It targets developers spending on LLM APIs who want to reduce costs. Planned features include live recommendations.
A developer open-sourced Token Harness, a local tool (Apache 2.0) that reduces token consumption by Claude Code and Codex agents. It installs optimizers that trim tool output, lazy-loads MCP tool definitions, and routes subtasks to cheaper models. The author reports 62.5% less tool output overall and 88.4% on Claude Code alone.
A developer open-sourced Token Harness, a local tool (Apache 2.0) that reduces token consumption by Claude Code and Codex agents. It installs optimizers that trim tool output, lazy-loads MCP tool definitions, and routes subtasks to cheaper models. The author reports 62.5% less tool output overall and 88.4% on Claude Code alone.
Promptster is a dashboard that analyzes how engineers use Claude Code and Codex, providing managers with aggregate code quality and workflow insights while giving engineers personalized coaching to save tokens without sacrificing output. It solves the problem of understanding and optimizing AI coding tool usage beyond basic spend and seat tracking.
Promptster is a dashboard that analyzes how engineers use Claude Code and Codex, providing managers with aggregate code quality and workflow insights while giving engineers personalized coaching to save tokens without sacrificing output. It solves the problem of understanding and optimizing AI coding tool usage beyond basic spend and seat tracking.