memory-curator

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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.

Install

mkdir -p .claude/skills/memory-curator && curl -L -o skill.zip "https://mcp.directory/api/skills/download/7524" && unzip -o skill.zip -d .claude/skills/memory-curator && rm skill.zip

Installs to .claude/skills/memory-curator

About this skill

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:

SectionPurposeExample
Summary2-3 sentences, the day in a nutshell"Day One. Named Milo. Built connections on Moltbook."
StatsQuick metricsLines, sections, karma, time span
Key EventsWhat happened (not everything, just what matters)Numbered list, 3-7 items
LearningsInsights worth rememberingBullet points
ConnectionsPeople interacted withNames + one-line context
Open QuestionsWhat you're still thinking aboutFor continuity
TomorrowWhat future-you should prioritizeActionable 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

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