Mature-agent compaction must handle triggers, complete-turn cut points, and recovery. looplane now has an 85% high-watermark, automatic compaction, a deterministic native-loop fallback summary, persisted checkpoints, and workspace-context reinjection. Cross-runtime fallback, model-quality summaries, and live-provider long-session validation remain open.
Near 85% context pressure, Looplane has two distinct paths: the native loop can apply one bounded deterministic history fallback, while a conversation runtime with native compaction can compact after a completed turn. Both paths re-anchor the next request with workspace context.
By default every DM lands in one main session, and group activity and background work report back into it. Memory is entirely Markdown on disk — the model only remembers what gets saved, with no hidden state. But if more than one person can DM your agent, DM isolation is something you have to turn on.
Claude Code loads the system prompt, MEMORY.md, CLAUDE.md, MCP tool names, and skill descriptions before you type your first word. This post breaks down the startup context, what each of six extension features costs, and how to control auto-compaction with /compact, /autocompact, and autoCompactWindow.