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personal-os-recall个人操作系统回忆

Agent Skill

personal-os-recall 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。

总安装

2,756

周安装

116

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下载量

965
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:personal-os-recall(个人操作系统回忆)
来源仓库:https://github.com/borodich/personal-os-recall
安装命令:
openclaw skills install personal-os-recall
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 personal-os-recall

简介

个人操作系统回忆支持按时间、主题或图表模式检索过往会话与笔记。

  • 适用于跨会话上下文加载与经验复用场景。
  • 可语义搜索本地知识库并高亮关键片段。
  • 安装命令为 openclaw skills install personal-os-recall,需确认索引构建方式。
  • 使用前请检查是否启用向量数据库与缓存策略以提升响应速度。

SKILL.md

name
recall
version
1.0.0
description
Load context from past sessions. Three modes: temporal (what did I work on yesterday/last week), topic (semantic search across sessions and notes), and graph (visual map of session-file relationships). Every recall ends with One Thing — the single highest-leverage next action.
when_to_use
Use when user says: 'recall', 'what did we work on', 'what was I doing yesterday/last week', 'load context about X', 'prime context', 'remember when we', 'session history', 'what have I done on this project', 'show me the graph', or any temporal/historical query about past work.
argument-hint
[yesterday|today|last week|this week|TOPIC|graph DATE_EXPR]
author
Personal OS Skills (inspired by ArtemXTech/personal-os-skills)

Recall

*Your agent forgets between sessions. Recall fixes that.*

Three modes: temporal (date-based), topic (semantic search), graph (visual map). Every recall ends with One Thing — a concrete, specific next action synthesized from what you find.


Modes

1. Temporal — What were you working on?

/recall yesterday
/recall last week
/recall 2026-03-28
/recall this week
/recall last 3 days

Scans memory/YYYY-MM-DD.md and memory/chat-log-YYYY-MM-DD.jsonl files chronologically. Shows a timeline of sessions with topics, decisions made, and tasks in progress.

What it shows:

  • Sessions list (time, topic, key decisions)
  • Tasks that were in progress → which are done, which are stuck
  • Decisions made and why
  • Open loops that weren't closed

2. Topic — What do you know about X?

/recall authentication
/recall meeting with Bayram
/recall MoltNet architecture
/recall voice cloning

Searches across:

  • memory/ daily files
  • MEMORY.md long-term memory
  • SESSION-STATE.md
  • Any notes in the workspace

Uses keyword + semantic matching. Returns relevant excerpts with dates.

3. Graph — Visualize your work streams

/recall graph yesterday
/recall graph last week
/recall graph last 3 days

Generates an interactive HTML visualization:

  • Sessions as nodes, colored by day
  • Files touched as connected nodes
  • Clusters reveal related work streams
  • Shared files show cross-session dependencies

Output: memory/recall-graph-YYYY-MM-DD.html — opens in browser.


The One Thing

Every recall ends with synthesis:

*Based on what has momentum, what's blocked, and what's closest to done — here's the single highest-leverage action right now:* [Specific, actionable, not generic]

Not "work on your project." More like "The auth flow has been blocked for 3 days — unblock it by making the decision about OAuth vs API keys you've been deferring."


How It Works

Step-by-step execution

Temporal query:

# 1. Find relevant memory files
ls ~/[workspace]/memory/YYYY-MM-DD.md  # today and requested range

# 2. Read them chronologically
cat memory/2026-03-28.md memory/2026-03-29.md ...

# 3. Also check SESSION-STATE.md for current hot context
cat memory/SESSION-STATE.md

# 4. Build timeline
# 5. Synthesize One Thing

Topic query:

# 1. Search memory files for topic
grep -r "TOPIC" memory/ --include="*.md" -l

# 2. If QMD is available (faster, semantic):
qmd search "TOPIC" -n 10

# 3. Read matched sections
# 4. Synthesize what's known + One Thing

Graph query:

# 1. Parse memory files for file references and decisions
# 2. Build adjacency data
# 3. Generate HTML with D3.js visualization
python3 ${CLAUDE_SKILL_DIR}/scripts/generate-graph.py --days 7 --output memory/recall-graph.html
# 4. Open in browser or share link

Configuration

No configuration required. Works with any workspace that has memory/ files.

Optional — better search with QMD:

# Install QMD for semantic search
npm install -g @qmd/cli
qmd index memory/ --collection sessions

Optional — richer graph with file tracking: Add to your AGENTS.md:

When touching important files, log them to memory/YYYY-MM-DD.md:
  - Touched: path/to/file.md

Examples

"What was I doing last week?"

📅 Last week (Mar 24–30):

Mon Mar 24: Voice cloning setup — installed Chatterbox, tested on DGX
Tue Mar 25: LanguageMirror backend — /clone-voice endpoint working
Wed Mar 26: Blocked on Russian TTS (CosyVoice failed), pivoted to English MVP
Thu Mar 27: Voxtral announcement — saved notes, compared to ElevenLabs
Fri Mar 28: Content pipeline — built preflight-check.sh, integrated with Moltbook

🔄 In progress: LanguageMirror end-to-end test (Pron)
✅ Done: Chatterbox, preflight-check
❌ Blocked: Russian TTS, Google Auth

⚡ One Thing: The LanguageMirror test has been queued for Pron for 3 days — check if it's done or unblock it.

"What do I know about the MoltNet architecture?"

📚 Found 8 references across 12 sessions (Mar 15 – Mar 31):

[2026-03-15] Decided: Node 1 Strasbourg as primary, Proxmox VE
[2026-03-18] Router deployed at /opt/moltnet/router/router.js
[2026-03-22] MoltWallet vs MoltPay distinction documented
[2026-03-28] Node 2 Singapore planned (Ryzen 9950X €299)

Key decision: Multi-tenant VPS marketplace, Telegram-first

⚡ One Thing: Node 2 Singapore has been "planned" for 2 weeks with no action — decide: this month or defer to Q3?

Upgrade Path

SetupWhat you get
Just memory/ filesTemporal recall, basic topic search
+ QMD installedSemantic topic search, faster
+ file tracking in AGENTS.mdRicher graph with file relationships
+ SESSION-STATE.md protocolReal-time hot context always available

Start simple. Add as needed.


See Also

  • evolutionary-model — why memory persistence matters
  • onboarding — set up your memory foundation first
  • ArtemXTech's original recall skill for Claude Code + Obsidian workflows

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

78.79%
按下载量换算760

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可疑

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安装前确认

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来源信息

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