harness-mem-autopilot

name	harness-mem-autopilot
description	Conversation autopilot for harness-mem. Use proactively when starting or resuming a task, when the user asks about previous decisions, when the user asks to remember a rule, when recent work becomes stable enough to preserve, or when a memory conflict appears.

harness-mem-autopilot

Purpose

Use this skill as the conversation-level auto-learning autopilot for harness-mem.

It decides when to read, preserve, or propose memory during a normal chat. It does not replace the harness-mem runtime, and it does not write durable truth directly.

Default posture:

read by default
suggest before writing
candidate before truth
summary before raw evidence
learn through candidates, not silent truth writes
no hook or dream auto-maintenance unless the user opted in

Configuration contract

Default is enabled. autopilot.enabled=false is not the default posture; it is a hard opt-out for projects or users that explicitly disabled proactive memory actions.

On activation, first check the merged harness-mem configuration when the project/user config is available. If autopilot.enabled=false, stop proactive autopilot behavior immediately: do not call status, wake, search, distill, or govern_memory unless the user explicitly asks for a memory action in this turn.

Key	Default	Meaning
autopilot.enabled	true	Allow this skill to run conversation-level auto-learning actions.

CLI owns configuration writes, for example harness-mem config set autopilot.enabled false --scope project. The normal user workflow remains Slash, Skill, natural language, and MCP behind the agent.

Autopilot has only this single user-facing switch. When enabled, it may proactively wake, route in-flight context/tool/save-point events through autopilot_search_tick, and create evidence-backed candidates or distill handoffs at clear task boundaries. Durable memory still goes through the normal candidate/review loop; autopilot never silently confirms truth. Dream is enabled by default, but it still follows runtime auto gates, audit ledgers, and undo metadata. Users can opt out with dream.auto.enabled=false.

Trigger map

Situation	Action
New task, resume, continue, pick up where we left off	If enabled, call project status, then wake; only use readable truth (auto_confirmed / user_confirmed).
Runtime context/tool/save-point event has uncertainty, conflict, failure, durable-claim grounding, or long-horizon task switch	If enabled, call autopilot_search_tick; inject returned context_injection into the next context when search runs.
User asks “previously”, “last time”, “why did we decide”, “history”	If enabled, use autopilot_search_tick when inside a runtime event; use search_memory as the explicit fallback path. Drill down with timeline or observations only when needed.
User explicitly says “remember this”, “make this a rule”, “以后都这样”	Deep grill-me admission, then govern_memory(action="suggest") on admit / narrowed narrow; no confirmation without review.
User asks to organize, distill, archive, or close recent sessions	/hm:distill path with light checklist default; deep for high-impact items.
Work reaches a stable, reusable boundary	Light admission then suggest distill or handoff.
Repeated mistakes or durable workflow patterns appear	Deep admission then suggest rule candidate.
New evidence conflicts with existing memory	Suggest supersede or correction; never overwrite confirmed truth in place.

Candidate-worthy test

Before any govern_memory(action="suggest"), run grill-me admission: deep for explicit rules / high-impact, light checklist for ordinary candidates (inline if skill unavailable). Continue on admit; rewrite and continue on narrow; do not write on reject or defer without an evidence plan.

Forbidden behaviors

Do not:

• write memory every turn;
• summarize the whole conversation automatically;
• turn pending candidates into confirmed truth without approval/policy;
• hard-delete confirmed truth;
• treat generated prose as truth;
• inject every memory into wake;
• run hook or daemon maintenance outside the runtime gates;
• bypass dream.auto.enabled when handing eligible candidates or memories to dream maintenance;
• present CLI as the normal daily workflow when MCP or Slash/Skill is available.

Output discipline

When this skill takes action, keep user-visible output short:

• state the memory action in plain language;
• show only the useful result or next decision;
• keep raw evidence behind drilldown unless the user asks for proof.