May 7, 2026 · Artificial Intelligence

How TACO Lets CLI Agents Self‑Evolve to Drop Useless Context

TACO is a plug‑and‑play, training‑free framework that lets terminal‑based autonomous agents automatically learn compression rules to filter low‑value output while preserving critical decision cues, achieving higher task success rates and better token efficiency across multiple terminal‑related benchmarks.

Code IntelligenceContext CompressionLLM

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How TACO Lets CLI Agents Self‑Evolve to Drop Useless Context

PaperAgent

May 3, 2026 · Artificial Intelligence

Skill Graphs Reveal Why Training Diversity Beats Quantity for Terminal Agents

The paper shows that, instead of increasing the number of training tasks, controlling the diversity of scene‑skill combinations via a large‑scale Skill Graph dramatically improves terminal‑agent performance, with Qwen3‑32B surpassing a 480B model on the Terminal‑Bench 2.0 benchmark.

LLMQwen3Skill Graphs

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Skill Graphs Reveal Why Training Diversity Beats Quantity for Terminal Agents