Agent Memory Implementation

Agent Memory Implementation is an AI Engineering skill for Claude Code, published by simbajigege in book2skills.

161 stars30 forkson simbajigege/book2skillsAdded 2026/09/08+4% in starsRepository updated 2026/08/26

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Install in seconds

Install Agent Memory Implementation

Copy Agent Memory Implementation into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/simbajigege/book2skills/tree/main/skills/agent-memory-implementation ~/.claude/skills/agent-memory-implementation

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/simbajigege/book2skills.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/agent-memory-implementation/SKILL.md in simbajigege/book2skills
Installs to: ~/.claude/skills/agent-memory-implementation
Collection: One of 25 skills cataloged from this repository
Category: AI Engineering — 3670 skills

What Agent Memory Implementation does

Agent Memory Implementation restructures a crowded MEMORY.md into a small pointer index plus on-demand topic files. Use it when MEMORY.md gets too long, mixes pointers with content, or needs stale memories corrected in place.

Agent Memory Implementation is cataloged under AI Engineering on DirSkills. Agent Memory Implementation comes from a repository tagged agent-skills, agentskills, anthropic, anthropic-claude and book2skills.

Documentation

README

Excerpt

memory-architect

Restructures memory files into the 2-layer architecture that Claude Code's autoDream service uses internally — designed to keep the always-loaded index small while making deeper knowledge accessible on demand.

The 2-Layer Architecture

Claude Code's memory system (services/autoDream/) uses this structure:

MEMORY.md          ← Layer 1: Always loaded, pointer-only index (~200 lines max)
├── topic-file.md  ← Layer 2: Domain knowledge, loaded when relevant
└── another-topic.md

Layer 1 — MEMORY.md index: Loaded into every conversation. Must stay under ~200 lines (lines beyond 200 get truncated). Each entry is a one-line pointer: - [Title](file.md) — one-line hook. No content, just pointers. This is what Claude scans to decide what to load.

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Agent Memory Implementation

What else does simbajigege publish alongside Agent Memory Implementation?
Agent Memory Implementation is one of 25 skills that DirSkills catalogs from simbajigege/book2skills, the repository it ships in. Its siblings there include Agent Tool Builder, Business Adventures Analysis and Common Sense Index Investing. Each one is a separate skill with its own page in this directory, installs the same way Agent Memory Implementation does, and is maintained by simbajigege in that same repository. The rest of the collection is listed on the simbajigege/book2skills page.
How does Agent Memory Implementation compare to other AI Engineering skills?
Agent Memory Implementation ranks #3403 by stars among the 3670 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Agent Memory Implementation against them. Open each page to compare what they document and how they install.