moai-cc-memory

Manages Claude session memory with just-in-time retrieval and layered context summaries.

1|Updated Jul 28, 2025

Search Tags:#context #memory #session #jit #memory-files

Ready to run

npx skills add https://github.com/kivo360/quickhooks --skill moai-cc-memory

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: moai-cc-memory
Source: https://github.com/kivo360/quickhooks/tree/main/.claude/skills/moai-cc-memory
Command: npx skills add https://github.com/kivo360/quickhooks --skill moai-cc-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill covers session memory optimization, JIT retrieval, and memory file organization to maximize context efficiency.

Core Features & Use Cases

Context Management: Just-in-time retrieval and memory caching.
Memory Files: Structured memory entries for quick handoff.
Session Handoff: Efficient transitions between tasks.

Quick Start

Create a memory entry detailing an ongoing feature and reference it in later steps.

Frequently Asked Questions about moai-cc-memory

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

FAQPage Schema

How do I manage context window overflow in long-running Claude Code sessions?▼

Context window overflow in extended sessions occurs when accumulated code, logs, and tool outputs exceed token limits. This Skill manages session memory through just-in-time retrieval, layered context summaries, and memory-file patterns to keep your working context within 100K–200K token windows while preserving access to prior work.

What are memory files and how do I use them for session handoffs?▼

Memory files are structured entries that capture ongoing task state, decisions, and file references for quick retrieval. Create a memory entry detailing your feature progress, then reference it in later steps to hand off context efficiently between sessions without reloading entire projects.

Can I use selective file loading and result caching to reduce context bloat?▼

Yes. Selective file loading loads only relevant files on demand rather than the entire project, while result caching stores computed outputs. Together with memory-file management, these techniques enable efficient workflow across large projects by controlling what stays in active context.

How do memory management and JIT retrieval work together in Claude Code?▼

Just-in-time retrieval fetches files and cached results only when needed, while memory management organizes session state into structured memory files. This combination prevents context bloat by deferring non-critical data retrieval until the task requires it.

Does this Skill work with Read, Write, Glob, and Bash tools?▼

Yes. This Skill is built to integrate with Read, Write, Glob, and Bash tools to enable efficient context management. These tools support selective file loading, memory-file operations, and result caching across your workflow.

When should I apply memory management to my workflow?▼

Apply memory management for long-running sessions, large projects, and cross-team handoffs where context budgeting is critical. It's essential when token usage approaches limits and you need reliable selective loading and memory-file patterns to maintain efficiency.