By devasher · Edited by Nominiclaw
This update focuses on per-agent local model configurations, critical fixes for LLM idle timeouts in cloud providers, and security hardening for update scripts.
One of the most significant updates is the introduction of per-agent local model lean mode. Through the new agents.list[].experimental.localModelLean configuration, users can now enable or disable "lean mode" for specific agents. This allows developers to trim heavy tool surfaces (such as browser, cron, and message) for specific local-model agents (e.g., those running via LM Studio) without affecting the main agent's capabilities.
Additionally, a critical fix was implemented for LLM idle timeouts. Previously, the models.providers.<id>.timeoutSeconds setting was ignored for cloud providers, capping timeouts at an implicit ~120s. This caused agents to abort long-running requests—such as those using Anthropic Opus with large tool payloads or Gemini preview models with silent reasoning buffers—even when users had explicitly configured longer timeouts. The system now correctly honors these user-defined ceilings for both local and cloud providers.
Security and stability improvements were rolled out across the CLI and Docker distribution:
nominiclawcodex plugin, which provides the default OpenAI agent harness, is now explicitly kept in official Docker release images to prevent runtime failures where the harness was previously pruned.acp client subcommand now uses formatErrorMessage to provide readable JSON diagnostics instead of the generic [object Object] output when encountering plain-object rejections.Several documentation updates clarify critical command behaviors and developer tools:
/new (which archives the current session and starts fresh) and /reset (which wipes the current session in place), correcting a previous error that labeled them as aliases.These changes directly address several user pain points regarding session data loss and LLM reliability. By clarifying the distinction between /new and /reset, users are less likely to accidentally wipe their session history. The fix for cloud provider timeouts removes a major "foot-gun" for power users employing high-token-count tool profiles or reasoning-heavy models.
From an operational standpoint, the hardening of the update restart scripts and the inclusion of the Codex plugin in Docker images reduce the risk of deployment failures and security vulnerabilities in temporary directories. Finally, the per-agent lean mode provides a more granular way to optimize local model performance, ensuring that limited-context local models are not overwhelmed by unnecessary tool definitions.