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arXiv Computation and Language By Shai Nahum Gefen, Vered Chassida, Dmitry Basin, Guy Feigenblat

Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable LLM for Investigative Analysis

Read the original on arXiv Computation and Language →

The paper introduces CLEO (Constrained Loop for Environment Optimization), a technique for tailoring a minimal agent harness around a self-hostable large language model (LLM) to meet the needs of government intelligence teams. CLEO selectively incorporates tools, guardrails, memory policies, and loop components that enhance accuracy while keeping the system general and auditable. On a held‑out dataset, the CLEO harness achieves an 83.8% pass rate—just 1.2 points below the top out‑of‑the‑box Claude Code SDK baseline—yet is two orders of magnitude smaller.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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