By devasher · Edited by Nominiclaw
This update focuses on fixing session loss during subagent compaction, enhancing iMessage and WhatsApp delivery, and refining Codex tool call transparency in transcripts.
Recent updates to OpenClaw have focused on strengthening the reliability of long-running agent sessions, refining the user experience across various messaging channels, and improving the observability of tool executions. These changes ensure that agents can maintain state across context window compactions and that users receive cleaner, more accurate feedback on mobile platforms.
One of the most critical fixes addresses a failure in subagent session management. Previously, when a subagent underwent context compaction, references to active background exec processes were lost, effectively orphaning the processes.
Subagent compaction loses running exec process references... the process session reference is lost. The actual process may continue running but becomes orphaned — the subagent can no longer poll/log/write to it.
To resolve this, OpenClaw now maintains a bounded runtime-owned snapshot of active background exec sessions, ensuring these references are preserved in rebuilt system prompts after compaction.
Several updates improve the reliability and clarity of messaging integrations:
nominiclawsend-rich --file. This allows agents to deliver files in a single threaded send rather than dropping them or throwing errors.thinking) to backend-advertised keys (like effort), preventing internal errors when updating session configurations.openai-codex/* routing in cron stores to align with the current openai/* canonical references.status and doctor commands now correctly recognize healthy LAN-bound Gateway listeners, eliminating false-positive port conflict warnings for users with internal reverse-proxy deployments.runtime-postbuild synchronization in watch mode to prevent the Gateway from launching with incomplete runtime trees when generated files are missing.These changes significantly improve the robustness of OpenClaw for professional use cases. The preservation of exec references allows agents to handle long-running data collection or training tasks without fear of context window limits interrupting their control. The improvements to WhatsApp and iMessage make the agent feel more native and less intrusive on mobile devices.
Furthermore, the mirroring of Codex tool calls into transcripts provides essential observability for developers benchmarking their models. By treating the transcript as the single source of truth, OpenClaw ensures that the actual behavior of the agent—including its internal tool-use trajectory—is fully auditable and reproducible.