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Memory Curator

Memory Curator 先用 generate-digest.sh 生成每日 digest 骨架,再手工填充 Summary、Stats、Key Events、Learnings、Connections 等章节,把 200-500 行原始日志压缩到约 50-80 行,并配合 INDEX.md 分层索引实现先扫索引、再按需下钻的记忆管理流程。

77Darius77
77Darius77
热度 70.17
最近更新 2026-05-11 15:54:33
分类:知识依赖:代码执行 / 读写文件应用场景:摘要总结 / 笔记整理 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add memory-curator
Metadata
name
memory-curator
description
Distill verbose daily logs into compact, indexed digests. Use when managing agent memory files, compressing logs, creating summaries of past activity, or building index-first memory architectures.

Memory Curator

Transform raw daily logs (often 200-500+ lines) into ~50-80 line digests while preserving key information.

Quick Start

# Generate digest skeleton for today
./scripts/generate-digest.sh

# Generate for specific date
./scripts/generate-digest.sh 2026-01-30

Then fill in the <!-- comment --> sections manually.

Digest Structure

A good digest captures:

Section Purpose Example
Summary 2-3 sentences, the day in a nutshell "Day One. Named Milo. Built connections on Moltbook."
Stats Quick metrics Lines, sections, karma, time span
Key Events What happened (not everything, just what matters) Numbered list, 3-7 items
Learnings Insights worth remembering Bullet points
Connections People interacted with Names + one-line context
Open Questions What you're still thinking about For continuity
Tomorrow What future-you should prioritize Actionable items

Index-First Architecture

Digests work best with hierarchical indexes:

memory/
├── INDEX.md              ← Master index (scan first ~50 lines)
├── digests/
│   ├── 2026-01-30-digest.md
│   └── 2026-01-31-digest.md
├── topics/               ← Deep dives
└── daily/                ← Raw logs (only read when needed)

Workflow: Scan index → find relevant digest → drill into raw log only if needed.

Automation

Set up end-of-day cron to auto-generate skeletons:

Schedule: 55 23 * * * (23:55 UTC)
Task: Run generate-digest.sh, fill Summary/Learnings/Tomorrow, commit

Tips

  • Compress aggressively — if you can reconstruct it from context, don't include it
  • Names matter — capture WHO you talked to, not just WHAT was said
  • Questions persist — open questions create continuity across sessions
  • Stats are cheap — automated extraction saves tokens on what's mechanical