Arxchibobo

Arxchibobo / memory-type-system

Public

OpenClaw AgentSkill from Claude Code analysis

15
11
100% credibility
Found Apr 01, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

A structured system for classifying personal memories or notes into four types with added details for better organization, recall, and relevance.

How It Works

1
💡 Discover the Memory Organizer

You're frustrated with jumbled notes and scattered ideas piling up, then you find this simple system to bring order to your thoughts.

2
📥 Bring It Home

You easily add this organizer to your personal workspace, ready to start sorting things out.

3
📝 Sort Memories into Types

You pick from four clear categories like user preferences, helpful feedback, project updates, or handy references to place each note perfectly.

4
✏️ Add Key Details

For each memory, you jot a quick name, description, and type, plus reasons why for feedback to make it super useful next time.

5
📋 Build a Clean Index

Your main list stays short and sweet, just pointers to the real memories, keeping everything tidy and easy to scan.

🎉 Thoughts Stay Sharp

Now your memories are organized, recalled accurately without junk, and always up-to-date to guide your decisions perfectly.

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AI-Generated Review

What is memory-type-system?

This OpenClaw agent skill brings a structured memory type system to AI coding assistants, classifying memories into user profiles, feedback with why/how, project decisions, and external references—all tagged with frontmatter for precise recall. It tackles memory bloat in tools like OpenClaw GitHub Copilot by turning a single MEMORY.md into a lean index (capped at 200 lines) that points to structured entries, cutting irrelevant noise and drift from outdated info. Install via git clone into your OpenClaw skills workspace to check system memory type and enable semantic searches across openclaw github releases or repos.

Why is it gaining traction?

Its killer hook is the "NOT-to-save" rules—six clear no-gos that prevent dumping junk—paired with mandatory why/how in feedback for reliable application. Unlike vague memory dumps in other openclaw github skills, frontmatter enables targeted retrieval without sifting noise, boosting signal in long sessions. Devs dig the Claude Code-inspired taxonomy for type systems for memory safety, making openclaw github integration feel smarter out of the box.

Who should use this?

AI-augmented coders on OpenClaw or similar agents handling multi-week projects, like backend teams tracking feedback loops or solo devs managing user prefs across refactors. Ideal for those frustrated with exploding memory files in openclaw github download workflows, especially when integrating external tools via reference types. Skip if you're not deep into agent skills or openclaw github stars chasing.

Verdict

With 15 stars and a 1.0% credibility score, it's raw and docs-light—great concept from Claude analysis, but test thoroughly before production. Worth a quick clone for OpenClaw users experimenting with system memory type; could mature into a staple if maintainers push releases.

(178 words)

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