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honcho-memory-muxhoncho 记忆 MUX

Agent Skill

honcho-memory-mux 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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下载量

3,584
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:honcho-memory-mux(honcho 记忆 MUX)
来源仓库:https://github.com/spooktheducks/honcho-memory-mux
安装命令:
openclaw skills install honcho-memory-mux
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install honcho-memory-mux

简介

honcho-memory-mux 扩展 Honcho 的记忆管理能力以支持上下文复用。

  • 可迁移旧版文件内存并优化代理工作区指令。
  • 适用于需要长期对话记忆的场景。honcho-memory-mux 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 使用前需备份原有内存数据以防丢失。
  • 注意与 OpenClaw 版本的兼容性及存储路径权限。

SKILL.md

name
honcho-memory-mux-setup
description
>
metadata
openclaw
emoji
🧠
optional_env
description
API key. Optional for many local/self-hosted setups.
description
Base URL for self-hosted Honcho (example: http://localhost:8000).
description
Honcho workspace ID (default: openclaw).
description
OpenClaw workspace root. Auto-detected if unset.
required_binaries
optional_binaries
writes_to_disk
true
network_access
homepage
https://honcho.dev
source

Honcho + Memory Mux Setup

This skill installs and enables: 1) @honcho-ai/openclaw-honcho (Honcho tools + integration) 2) @alloralabs/honcho-memory-mux (multiplexed memory behavior)

Then it migrates legacy memory files, updates agent docs, and validates runtime behavior.


What “memory mux” means in practice

After setup, memory behavior should be:

  • Primary retrieval: Honcho tools (honcho_context, honcho_search, etc.)
  • Secondary retrieval: local memory files (MEMORY.md, memory/*.md) via memory_search / memory_get
  • Durability: pre-compaction flush writes significant session learnings to memory/YYYY-MM-DD.md
  • Fallback safety: if Honcho is unavailable, file-based memory still works

This is intentionally complementary, not a hard cutover.


Step 0: Preflight and safety checks

Before doing anything destructive:

  • Resolve workspace root from:

1. WORKSPACE_ROOT 2. ~/.openclaw/openclaw.json (agent.workspace or agents.defaults.workspace) 3. ~/.openclaw/workspace

  • Confirm directory exists
  • Inform user this process can upload memory files to Honcho

Step 1: Install + enable Honcho plugin

Use OpenClaw plugin manager (not workspace npm install):

openclaw plugins install @honcho-ai/openclaw-honcho
openclaw plugins enable openclaw-honcho

If gateway logs show missing SDK deps:

cd ~/.openclaw/extensions/openclaw-honcho
npm install

Restart gateway if required.


Step 2: Install + enable memory mux extension

Install and enable the memory-mux extension:

openclaw plugins install @alloralabs/honcho-memory-mux
openclaw plugins enable @alloralabs/honcho-memory-mux

If the extension is local/unpublished, install from path or git URL per your release flow.

After enabling:

  • Verify plugin appears in openclaw plugins list
  • Verify gateway boots cleanly (no extension load errors)
  • Verify both Honcho tools and memory_search / memory_get are present at runtime

Step 3: Verify Honcho connectivity (self-hosted)

  • Set HONCHO_BASE_URL (example: http://localhost:8000)
  • HONCHO_API_KEY may be optional depending on auth config

If user needs local Honcho quickly:

git clone https://github.com/plastic-labs/honcho
cd honcho
cp .env.template .env
cp docker-compose.yml.example docker-compose.yml
docker compose up -d

Do not migrate until connection is verified.


Step 4: Detect and classify legacy memory files

Scan workspace for:

User/owner memory inputs

  • USER.md
  • IDENTITY.md
  • MEMORY.md
  • memory/** (recursive)
  • canvas/** (recursive)

Agent/self memory inputs

  • SOUL.md
  • AGENTS.md (and AGENT.md if present in this workspace)
  • TOOLS.md
  • BOOTSTRAP.md
  • HEARTBEAT.md

Present a clear preview before upload:

  • count files per class
  • total bytes per class
  • any unreadable/skipped files

Ask for explicit confirmation.


Step 5: Upload to Honcho using peer-separated sessions

Create/ensure:

  • workspace (HONCHO_WORKSPACE_ID or openclaw)
  • peer owner
  • peer openclaw
  • migration session (e.g. migration-upload-<timestamp>)

Add both peers to session, then upload files:

  • user/owner files → owner
  • agent/self files → openclaw

If any upload fails:

  • stop
  • report exact file and error
  • keep local files unchanged

Report summary:

  • uploaded user file count
  • uploaded agent file count
  • failed/skipped files

Step 6: Update workspace docs (including AGENT.md compatibility)

Update/create memory instructions in:

  • AGENTS.md
  • SOUL.md
  • BOOTSTRAP.md
  • AGENT.md (if this workspace uses it)

Preserve custom content; only replace memory-specific sections.

Required policy text to add

  1. Memory retrieval order

- First try honcho_context / honcho_search / honcho_recall - If needed, use memory_search + memory_get for local file recall - Use honcho_session for same-session recall

  1. Memory write behavior

- Important durable facts can be written via honcho_write - Pre-compaction flush writes concise durable notes to memory/YYYY-MM-DD.md

  1. Failure handling

- If Honcho unavailable: continue with local memory tools, state degraded mode - Never claim memory certainty without retrieval evidence

  1. Transparency

- When memory influences an answer, be able to explain source class (Honcho recall vs local file recall vs current-session context)


Step 7: Add/refresh practical memory operating conventions

Ensure docs reflect these conventions the agent has been using:

  • Do not preload everything into active reasoning if not needed
  • Prefer targeted retrieval over huge static context injection
  • Treat disagreement as signal: preserve conflicting observations; do not silently average
  • Use pre-compaction flushes to avoid losing high-value context during long sessions
  • Separate memory types conceptually:

- durable facts - episodic notes - scratch/working notes

Even if physical storage is mixed, behavior should preserve this distinction.


Step 8: Optional (recommended) no-fork observability add-on

Without modifying OpenClaw gateway source, the memory-mux extension can emit:

  • a small memory load manifest per session start (what memory sources were pulled)
  • a pre-compaction write report (what was persisted)

Store under:

  • memory/manifests/YYYY-MM-DD/<session>.json

This makes memory behavior debuggable while keeping upstream updates painless.


Step 9: Validate end-to-end behavior

Run a quick live test:

  1. Ask agent about a known historical fact only in migrated memory
  2. Confirm retrieval path works (Honcho first, fallback available)
  3. Trigger/perform pre-compaction flush
  4. Confirm new note appears in memory/YYYY-MM-DD.md
  5. Re-ask fact in a new turn/session to validate durability

Wrap-up report to user

Provide:

  • installed/enabled plugin list
  • Honcho connectivity mode (managed vs self-hosted)
  • files discovered, uploaded, skipped
  • docs updated (AGENTS.md, SOUL.md, BOOTSTRAP.md, AGENT.md if present)
  • any follow-up actions

Reference docs:

  • https://docs.honcho.dev
  • https://github.com/plastic-labs/honcho

Guardrails

  • Never delete user memory files automatically unless user explicitly asks
  • Never proceed with migration on failed Honcho connectivity
  • Never silently ignore upload errors
  • Prefer reversible edits and clear summaries

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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安装前确认

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