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Background memory compaction with auto-trigger, chat summary paragraph, configurable threshold, model selector, settings tab, and result storage for OpenClaw Control UI.
Passed 15 of 19 test cases with the skill, and 1 of 19 without it.
16 fixed1 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
The instructions your model reads when the skill loads.
Memory compaction system for the OpenClaw Control UI — background execution with toast notifications, auto-trigger at configurable token thresholds, conversation summary paragraphs in compacted output, dedicated settings tab with model selector, and result history.
| Component | Status |
|---|---|
| Context Gauge Button | ✅ Working |
| Background Compaction (toast) | ✅ Working |
| Auto-Compaction Trigger | ✅ Working |
| Conversation Summary Paragraph | ✅ Working |
| Settings Tab (plugin-registered) | ✅ Working |
| Model Selector | ✅ Working |
| Last Result Storage + Viewer | ✅ Working |
| Settings Persistence & Reload | ✅ Working |
| Auth Hierarchy (OAuth > API > Fallback) | ✅ Working |
| Chat History Filters | ✅ Working |
| Full Background Isolation (no chat interference) | ✅ Working |
app-render.helpers.ts)A circular SVG progress ring in the chat toolbar that doubles as the manual compact trigger.
renderChatControls()sessionsResult.sessions[].totalTokens and contextTokens from session rowsOn click (or auto-trigger), compaction runs in the background using the standard bottom-right toast system — no blocking modal. The UI remains fully interactive.
backgroundJobToasts system consistent with all other background processes (cron, knowledge extraction, etc.)test cases passed, vs 1 / 19 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.