TokenEconomizer cuts coding agent costs up to 30.9%
MarkTechPost: Meet TokenEconomizer: Microsoft’s Plugin That Cuts Coding Agent Costs by Up to 30.9%
A team of researchers from Microsoft Research and UC Berkeley have released TokenEconomizer, an open-source cost controller for coding agents. TokenEconomizer is a plugin that learns from past sessions in a repository to cut waste in later ones. It works with Claude Code, Codex, GitHub Copilot CLI and Pi. It does not touch model weights or agent code. On 277 SWE-Bench tasks, it lowered mean cost by 18.4% to 30.9% across 5 agent-model settings. TL;DR Package: A standard-library Python pac
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TokenEconomizer is an open-source plugin that reduces the cost of running coding agents by learning from past work sessions in a repository and applying three cost-cutting strategies: extracting reusable facts from earlier traces, removing unused tool schemas, and stopping agents caught in failure loops. On standard coding benchmarks, the plugin achieved cost reductions between 18.4% and 30.9% across different agent and model combinations without modifying the underlying agent code or model weights. The plugin works with multiple coding agents including Claude Code, Codex, GitHub Copilot CLI, and Pi, and installs as a standard Python package that stores learned data locally on the user's machine.
Explainer: The 90% That Matters: Why Your Agent's Harness Beats the Model
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