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autodreamautodream 分析

Agent Skill

autodream 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

4,742

周安装

190

GitHub Stars

公开资料未说明

下载量

1,535
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:autodream(autodream 分析)
来源仓库:https://github.com/rimaslogic/autodream
安装命令:
openclaw skills install autodream
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 autodream

简介

自动整理代理日常记忆文件减少冗余。

  • 删除重复项并规范化日期格式信息。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 建立清晰可追溯的知识演进路径。autodream 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 定期运行以维持内存系统高效运作。
  • 重要数据变更前建议手动备份存档。

SKILL.md

name
autodream
description
>-
metadata
openclaw
emoji
🌙
requires
anyBins
["node"]

Autodream — Memory Consolidation

Consolidates scattered daily memory files into a clean, organized MEMORY.md.

When to Use

  • Manually: User says "consolidate memory", "dream", "clean up memory", "organize my memories"
  • Via heartbeat: Periodically check if consolidation is needed (24h+ since last run AND 5+ new files)
  • After major events: Big refactor, project changes, many new daily files

Quick Start

# Check if consolidation is needed
node /path/to/openclaw-autodream/bin/autodream.js {{workspace}} --stats

# Run consolidation (dry run first!)
node /path/to/openclaw-autodream/bin/autodream.js {{workspace}} --dry-run --verbose

# Run for real
node /path/to/openclaw-autodream/bin/autodream.js {{workspace}} --verbose

# Force full reconsolidation
node /path/to/openclaw-autodream/bin/autodream.js {{workspace}} --force --verbose

Replace {{workspace}} with your actual workspace path (e.g., ~/.openclaw/workspace).

If Installed Globally

# npm install -g openclaw-autodream
autodream ~/.openclaw/workspace --stats
autodream ~/.openclaw/workspace --verbose
autodream ~/.openclaw/workspace --dry-run

What It Does (4 Phases)

Phase 1: Orientation

  • Reads existing MEMORY.md (if any)
  • Scans memory/ for daily files
  • Identifies files changed since last consolidation

Phase 2: Gather Signal

  • Extracts structured entries from each daily file
  • Classifies into categories: People, Projects, Preferences, Technical Decisions, Events, Lessons
  • Scores importance of each entry

Phase 3: Consolidation

  • Removes exact duplicates (hash-based)
  • Removes fuzzy duplicates (similarity > 75%)
  • Prunes stale entries (completed tasks, old debugging notes)
  • Normalizes relative dates ("yesterday" → "2026-03-24")

Phase 4: Prune & Index

  • Enforces max line limit (default: 200 lines)
  • Prioritizes by importance × recency
  • Writes clean MEMORY.md with category sections
  • Backs up previous MEMORY.md to memory/.autodream-backups/

Heartbeat Integration

Add to your HEARTBEAT.md:

## Memory Consolidation Check
- Run `autodream <workspace> --stats` to check if consolidation is needed
- If "Would trigger: ✅ yes", run `autodream <workspace> --verbose`
- Only run consolidation during quiet hours (not while human is actively chatting)

Configuration

Create .autodream.json in workspace root to customize:

{
  "maxLines": 200,
  "lookbackDays": 30,
  "categories": [
    "People & Relationships",
    "Projects & Work",
    "Preferences & Style",
    "Technical Decisions",
    "Important Events",
    "Lessons Learned"
  ],
  "preservePatterns": ["⚠️", "IMPORTANT", "NEVER", "ALWAYS"],
  "triggerThreshold": {
    "minHoursSinceLastRun": 24,
    "minNewFiles": 5
  }
}

Safety

  • Non-destructive: Always backs up existing MEMORY.md before modifying
  • Backups: Stored in memory/.autodream-backups/
  • Reports: Consolidation reports in memory/.autodream-reports/
  • Dry run: Always available with --dry-run
  • Protected entries: Entries with ⚠️, IMPORTANT, NEVER, ALWAYS are never pruned

Output Format

# Long-Term Memory
<!-- Last consolidated: 2026-03-25T17:00:00Z | Files processed: 31 | Entries: 47 -->

## People & Relationships
- **Bob Smith** — Team Lead test run passed (2026-03-25)

## Projects & Work
- **Acme Corp** — Q1 review: 30.1% margin, targeting 40% (2026-03-25)

## Preferences & Style
- Values precision and factual accuracy (2026-02-01)

## Technical Decisions
- Using Supabase + Vercel for Project Alpha (2026-03-18)

## Lessons Learned
- Always backup before modifying production data (2026-02-15)

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

82.56%
按下载量换算1,267

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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