memory-engram

Persist and retrieve memory entries across sessions using mem_save, mem_context, and mem_search.

Updated Mar 25, 2026

Search Tags:#context #ai #memory #persistence #session #mem_save

Ready to run

npx skills add https://github.com/MileniumTick/skills --skill memory-engram

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: memory-engram
Source: https://github.com/MileniumTick/skills/tree/main/skills/memory-engram
Command: npx skills add https://github.com/MileniumTick/skills --skill memory-engram

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Engram provides a persistent memory protocol to save and retrieve context across sessions, enabling continuity in AI-assisted development workflows.

Core Features & Use Cases

Persist decisions, architecture changes, and user preferences between sessions.
Store contextual observations and learnings to recall when needed, improving consistency across interactions.
Use cases include remembering coding conventions, project decisions, and frequently cited constraints.

Quick Start

Use mem_save to record a memory entry after a significant decision or discovery.

Frequently Asked Questions about memory-engram

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

FAQPage Schema

How do I persist context across AI coding sessions?▼

You persist context across sessions by using a dedicated memory protocol to save and retrieve development decisions. It records architecture changes and user preferences to maintain workflow continuity.

What is the best way to save AI memory entries during development?▼

The best way to save AI memory entries is to record a structured payload after a significant discovery. You apply a storage function to capture the title, type, scope, and content of the contextual observation.

How do I retrieve stored context for AI-assisted coding projects?▼

You retrieve stored context by applying specific memory retrieval functions to search saved entries. This recalls past decisions and constraints, ensuring consistency across your current workflow.

Can I store structured payloads with title and scope in persistent memory?▼

Yes, you can store structured payloads in persistent memory. The protocol supports saving entries that include specific fields for title, type, scope, and content to accurately categorize contextual data.

Why does my AI assistant forget coding conventions between sessions?▼

Your AI assistant forgets coding conventions because it lacks a persistent memory protocol. By saving these constraints as structured entries, you can recall them during future interactions to maintain consistency.