ReMe/reme-plugin/plugins/reme-service

reme-service

Service-tier markdown vault management for Claude Code. Three high-level MCP tools — retrieve / remember / maintain — backed by reme2's internal Ingestor + Maintainer. The agent calls the tools with intent; the LLM-driven R-M-W loop (Distill) and the sweep loop (Maintain) run inside reme2.

For the agentic alternative where Claude Code's own subagents run those loops outside reme2, install reme-expert instead.

Install

/plugin marketplace add /Users/huangsen/codes/ReMe/reme-plugin
/plugin install reme-service

export VAULT_PATH=/path/to/your/vault

What's in the box

MCP server (reme)

Three tools projected from the three memory services (reme2/config/service.yaml):

Tool	Phase	Backend
retrieve(query, max_results?, graph_depth?, seeds?, ...)	Recall	thin (memory_graph_search)
remember(mode=log|distill, name?, content, materials?, related_paths?, ...)	Log / Distill	sync upsert (mode=log, no LLM) / Ingestor's internal ReActAgent (mode=distill)
maintain(target_prefix?, ops?, dry_run?, decay_days?)	Maintain	Maintainer class

Skill

reme-service (auto-invoked) — describes the 4-phase paradigm (Recall / Log / Distill / Maintain) and how each phase maps to the three tools. Symmetrical with reme-expert's skill: same chapter structure, same triggers, just different tools to call.

Hooks (parallel to reme-expert)

Event	Action
PreCompact	Prompt: call remember(mode=log, materials=[...]) to dump volatile state into the current thread's event folder, reusing the thread's name for upsert; then output a compression guide.
SessionEnd	Prompt: call remember(mode=log) to capture remaining facts, then call remember(mode=distill, related_paths=[...]) once to hand off the working set to the Ingestor.
Stop	active_events_check.py — warns via stderr if any status: active events remain, suggests remember(mode=distill).

There are no SessionStart / UserPromptSubmit auto-recall hooks — the agent's skill tells it when to call retrieve itself, which is more accurate than blanket injection.

Layout

plugins/reme-service/
├── .claude-plugin/plugin.json
├── .mcp.json                       # config=reme2/config/service.yaml
├── protocol.md                     # canonical protocol, transcluded by SKILL via @../../protocol.md
├── skills/reme-service/SKILL.md
├── hooks/
│   ├── hooks.json                  # PreCompact / SessionEnd / Stop
│   └── active_events_check.py
└── README.md                       # this file

.mcp.json resolves the sibling reme2/ package via PYTHONPATH=${CLAUDE_PLUGIN_ROOT}/../../.. (marketplace root → repo root). No pip install needed.

protocol.md is a copy of the canonical reme2/memory/protocol.md. The same file is read by reme2's internal Ingestor (injected as {protocol} into the ReActAgent's sys_prompt) — this plugin ships its own copy so the SKILL's @../../protocol.md transclusion works after marketplace install.

Workflow at a glance

对话过程            → 模型按需调 retrieve（intent-driven）
任务执行中          → remember(mode=log) 持续 upsert；materials 装原始素材（确定性、零 LLM）
PreCompact (hook)  → 提示调 remember(mode=log) dump materials + 输出压缩指引
任务完成           → remember(mode=distill) 一次 → Ingestor 内部 ReActAgent 跑 R-M-W → 返回 audit
SessionEnd (hook)  → 提示 remember(mode=log) 收尾 + remember(mode=distill) handoff
Stop (hook)        → active_events_check.py 提醒未 distill 的 active events
periodic           → maintain(dry_run=true) 看一眼，必要时 dry_run=false 应用

When to switch to expert mode

The service plugin hides the schema, claim confidence, wikilink uniqueness, path templates, and status state machine — remember(mode= distill) enforces them all underneath. Switch to reme-expert when:

• You need fine-grained control over what gets created/edited.
• You want every memory mutation visible in the main session's tool log (vs hidden inside the Ingestor's internal ReActAgent).
• You want subagents to handle distillation as bounded background work with their own context windows.