Compact Memory Implementation

Compact 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 Compact Memory Implementation

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

What Compact Memory Implementation does

Compact Memory Implementation shows how to add memory compaction to an agent by triggering a forked compactor, generating a structured summary, and restoring it in later sessions. Use it when building context compression or persistence with Claude Agent SDK or the Anthropic API.

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

Documentation

README

Excerpt

compact-memory-implementation

A developer guide for building compact memory into an Agent: detect when to compress, fork a compactor sub-agent, produce a structured summary, and restore it in the next session.

Step 1 — Understand the setup

Before designing anything, clarify:

SDK / language: Claude Agent SDK? Direct Anthropic API? Python or TypeScript?
Agent architecture: single-agent loop, multi-agent, tool-calling?
Session model: one long-running session or multiple short sessions?
What must survive compaction: task state, decisions, tool results, conversation history?

This determines which pattern fits.

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

Frequently asked about Compact Memory Implementation

What else does simbajigege publish alongside Compact Memory Implementation?
Compact Memory Implementation is one of 25 skills that DirSkills catalogs from simbajigege/book2skills, the repository it ships in. Its siblings there include Agent Memory Implementation, Agent Tool Builder and Business Adventures Analysis. Each one is a separate skill with its own page in this directory, installs the same way Compact 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 Compact Memory Implementation compare to other AI Engineering skills?
Compact Memory Implementation ranks #3415 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 Compact Memory Implementation against them. Open each page to compare what they document and how they install.