#417 · Primary category: AI Coding Assistants

tura

agent agentic-ai coding-agent context-engineering developer-tools developer-tools-ai-agent harness-engineering llm mcp terminal-based token-optimization token-usage

Build agent that uses 80% less token and delivers better results.

Project last updated:08/20/26

GitHub Stars

605

Forks

32

Contributors

6

License

AGPL-3.0

Why we included this project

Tura is a terminal-based coding agent built around a simple idea: much of what an agent spends on tokens goes to context it carries through the loop, not to the work itself. Instead of having the model re-enter after every tool result, it compiles the task into a runtime-managed command graph and runs several steps in a single turn. The project publishes benchmark numbers to back that up, reporting 77.5% fewer tokens than Codex CLI on DeepSWE v1.1 tasks with a comparable verifier success rate, and a balanced mode that spends some of the savings on more reasoning and reaches a higher success rate. For developers and small teams whose agent bills are climbing, or who are tired of watching an agent patch a repo before it understands the goal, Tura is worth testing against your own long-horizon tasks.

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