Lossless Claw is now supported in OpenClaw Setup

You can now enable Lossless Claw as the context engine for your hosted OpenClaw instance. It replaces blunt sliding-window compaction with a lossless context system that preserves full conversation history while still fitting within model token limits.

What shipped

• Hosted Lossless Claw toggle: enable the @martian-engineering/lossless-claw plugin from Instance Settings.
• Context engine wiring: OpenClaw Setup now sets plugins.slots.contextEngine = "lossless-claw" for you.
• Sane hosted defaults: the plugin starts with recommended compaction settings for fresh-tail protection and aggressive DAG condensation.
• Managed first-run install: when you enable it on a running instance, Setup installs the plugin into the pod and restarts cleanly.
• QMD-compatible setup: you can keep QMD memory enabled while using Lossless Claw for context compaction.
• Import awareness: importing an existing OpenClaw archive now detects Lossless Claw and carries that preference into the hosted preview flow.

What it enables

In standard agent setups, long conversations eventually force the model to drop older messages or compress them so aggressively that details disappear. Lossless Claw takes a different approach. It stores the full history, summarizes older chunks into a DAG, and assembles the next turn from recent raw messages plus structured summaries. The practical effect is simple: your assistant keeps continuity much better as conversations get longer.

It also exposes retrieval tools over compacted history, so the agent can search or expand older material instead of behaving as if earlier context vanished. That makes long-running research, support, operations, and project threads much more viable than a pure sliding window. The original project lives on GitHub here.

Why this matters in hosted OpenClaw

Upstream, Lossless Claw is interesting because it upgrades OpenClaw’s context behavior. In a managed product, it is more than that: it removes the annoying parts of adopting it. You do not need to shell into the instance, manage plugin install commands by hand, or remember the exact config shape for the context engine slot.

OpenClaw Setup handles the install path, persists the enablement flag, regenerates the runtime config, and restarts the instance with the right plugin state. The result is that you can try a much more capable conversation-memory strategy without turning your hosted instance into a maintenance project.

Best fit use cases

• Assistants that stay in the same project thread for days or weeks
• Telegram or Slack workflows where continuity matters more than one-shot answers
• Research and planning sessions that need recall of older decisions
• Operator or founder copilots where “we already discussed this” is a normal part of work

Operational notes

Lossless Claw improves history preservation during compaction, but it does not change OpenClaw’s core session reset rules on its own. If you want long-lived continuity, pair it with sensible session reset settings for your channel and workload. In OpenClaw Setup, the first enablement also requires the instance to be running so the plugin can be installed.