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memory-curator

Compress verbose daily agent logs into compact indexed digests.

2|1|Updated Feb 13, 2026
Search Tags:#summarization#memory management#agent logs#log compression#digest generation#index-first
One-click install
npx skills add https://github.com/simplefarmer69/ape-claw --skill memory-curator-simplefarmer69
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-curator
Source: https://github.com/simplefarmer69/ape-claw/tree/main/data/forge-skills/clawhub-memory-curator
Command: npx skills add https://github.com/simplefarmer69/ape-claw --skill memory-curator-simplefarmer69

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of managing large, verbose agent memory logs by distilling them into compact, easily digestible summaries.

Core Features & Use Cases

  • Log Compression: Reduces lengthy daily logs (200-500+ lines) to concise digests (50-80 lines).
  • Information Preservation: Ensures key information, events, and learnings are retained.
  • Memory Architecture: Facilitates index-first memory systems for efficient retrieval.
  • Use Case: An agent generates extensive logs daily. This skill processes these logs into a summarized digest, making it easier for a human operator to quickly understand the agent's activity, key decisions, and outcomes without reading through hundreds of lines of raw data.

Quick Start

Run the ./scripts/generate-digest.sh script to create a digest for today's activities.

Frequently Asked Questions about memory-curator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compress verbose agent logs into a concise summary?▼

You can compress verbose agent logs by running a shell script that distills 200-500+ line activity records into compact 50-80 line digests. This process retains key events and learnings while significantly reducing overall volume for efficient memory management.

What is an index-first memory architecture for agent logs?▼

An index-first memory architecture organizes compressed agent log digests around a searchable index for efficient retrieval. This approach ensures past activity summaries are quickly accessible without scanning hundreds of raw log lines.

How do I generate a daily digest from agent activity logs?▼

To generate a daily digest, run the provided shell script to process today's agent activities. After the script generates the initial output, you must manually fill in the summary, learnings, and tomorrow sections to complete the digest.

Can I use log compression for daily agent logs with hundreds of lines?▼

Log compression is designed specifically for daily agent logs spanning 200 to 500 or more lines. It reduces these verbose records to concise 50-80 line digests while ensuring key information and outcomes are preserved.

Do I need to manually edit agent log digests after generation?▼

Yes, manual editing is required after script generation. You must manually fill the summary, learnings, and tomorrow sections to ensure the compressed digest accurately captures key decisions and outcomes.

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