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lucid-dreamer清醒梦者

Agent Skill

lucid-dreamer 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

总安装

8,911

周安装

364

GitHub Stars

公开资料未说明

下载量

2,883
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:lucid-dreamer(清醒梦者)
来源仓库:https://github.com/robbyczgw-cla/lucid-dreamer
安装命令:
openclaw skills install lucid-dreamer
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 lucid-dreamer

简介

lucid-dreamer 作为夜间推理系统,自动分析笔记并更新知识库。

  • 适合需要持续学习、事实修正和待办事项跟踪的智能助手场景。
  • 每晚离线运行,检测过时信息和未完成任务,生成优化建议。
  • 安装需配置定时任务和文件读写权限,建议隔离敏感数据目录。
  • 注意避免在低电量设备上启用,以防影响系统稳定性。

SKILL.md

name
lucid-dreamer
version
0.7.8
description
Nightly AI memory reasoning system. Lucid runs every night while you sleep — it reads your daily notes and memory files, detects stale facts, unresolved todos, recurring problems, forgotten decisions, and can optionally perform aggressive cleanup and contradiction detection. Includes optional session debrief for quick end-of-day memory capture. Zero dependencies, no database, no embeddings. Just a cron job and markdown files. Use when you want your AI agent to automatically maintain and improve its long-term memory over time. Triggers on \"memory dreamer\", \"nightly memory review\", \"lucid\", \"auto memory\", \"memory cleanup\", \"memory hygiene\".
metadata
{"openclaw":{"requires":{"bins":["git","date","python3"],"note":"Set CLAWD_DIR to your workspace path before running. Auto-apply and aggressive cleanup are disabled by default. python3 required for trend detection."}}}

Lucid Dreamer 🧠

*Your AI sleeps. Lucid dreams.*

Lucid keeps your AI's memory clean. Every night, it reads what happened, checks what your AI already knows, and suggests what's outdated, missing, or forgotten.

See README.md for full setup, ARCHITECTURE.md for internals, and config/ for configuration.

Quick Setup

  1. Set your workspace path in the config:
   export CLAWD_DIR=/path/to/your/workspace
  1. Create a nightly cron job using OpenClaw's cron tool — run the prompt in prompts/nightly-review.md at 3 AM.

Optional: add a lightweight session debrief cron around 18:00 using prompts/session-debrief.md. This is a faster daily capture pass than the nightly review — it reads today's daily note and writes durable decisions/facts straight into memory without creating a review report.

  1. Wake up to a review report in memory/review/YYYY-MM-DD.md.
  1. Approve or reject suggestions — Lucid tracks state in memory/review/state.json.

Optional Session Debrief Cron

Use prompts/session-debrief.md for a quick end-of-day memory pass around 18:00. It is designed to run faster than the nightly review: read today's daily note, capture durable decisions/facts/action items, and write them directly into memory.

Recommended OpenClaw cron settings:

openclaw cron add \
  --name "lucid-debrief" \
  --cron "0 18 * * *" \
  --tz "Europe/Vienna" \
  --model "your-preferred-model" \  # e.g. anthropic/claude-haiku-4-5 or opencode-go/minimax-m2.7
  --session isolated \
  --wake-mode now \
  --message "$(cat prompts/session-debrief.md)"

What it does:

  • Reads today's daily note (memory/TODAY.md)
  • Captures key decisions, durable facts, and concrete action items
  • Writes those updates directly into long-term memory
  • Skips the full review report to stay quick and cheap

Files

  • prompts/nightly-review.md — the main nightly review prompt
  • prompts/session-debrief.md — optional quick-capture prompt for ~18:00
  • config/ — thresholds and behavior settings
  • examples/ — sample review output and state file

Security

Files read at runtime:

  • MEMORY.md — long-term agent memory summary
  • USER.md — user profile and preferences
  • Last 7 daily notes (memory/YYYY-MM-DD.md)

Files written at runtime:

  • memory/review/YYYY-MM-DD.md — the generated review report
  • memory/review/state.json — approval/rejection tracking state

What this skill is designed to avoid:

  • Avoid suggesting or outputting passwords, API keys, tokens, or other credentials in generated memory updates
  • Never accesses files outside the configured workspace directory
  • Never pushes to remote git automatically — all commits are local only, and no git push is performed unless you explicitly run it
  • Announce/notification delivery is opt-in and off by default — no messages are sent without explicit configuration

Recommendations:

  • Set CLAWD_DIR explicitly in your environment to ensure the skill operates on the correct workspace
  • This skill reads workspace markdown files such as MEMORY.md, USER.md, and recent daily notes. Do not run it on a workspace containing unencrypted API keys or other secrets in plain markdown files.
  • Review generated reports before approving suggestions — Lucid proposes changes, but you remain in control

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

OpenClaw

86.86%
按下载量换算2,504

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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