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BRANDNEWSHVT
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persistent-memory

Automate persistent memory across AI agent sessions using file-based storage.

Updated Aug 20, 2025
Search Tags:#planning#persistent-memory#session-context#memory-management#ai-memory#agent-logging
One-click install
npx skills add https://github.com/BRANDNEWSHVT/mercora --skill persistent-memory-brandnewshvt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: persistent-memory
Source: https://github.com/BRANDNEWSHVT/mercora/tree/main/storefront-nuxt/.agents/skills/persistent-memory
Command: npx skills add https://github.com/BRANDNEWSHVT/mercora --skill persistent-memory-brandnewshvt

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Automated context preservation across AI coding sessions — no hooks or external services required. This skill provides a file-based memory protocol that lets any agent read/write files to remember decisions, context, and learnings across sessions.

Core Features & Use Cases

  • Agent-agnostic memory: preserves context across sessions using a universal file-based store.
  • Memory stack: organizes brain like MEMORY.md, sessions/, decisions/, context/, and handoffs/ to keep history compact and compressible.
  • Deterministic workflows: optional scripts/references/assets enable reproducible memory management and handoffs.

Quick Start

Boot the memory system by running the memory initialization workflow, then begin recording decisions, context, and learnings to MEMORY.md and its session logs for cross-session recall.

Frequently Asked Questions about persistent-memory

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

FAQPage Schema
How do I preserve context across AI coding sessions without external services?▼

To preserve context across AI coding sessions without external services, use a file-based memory protocol that reads and writes decisions and context directly to local files like MEMORY.md and session logs.

Does this persistent memory system work with agents like Cursor and Claude Code?▼

Yes, this persistent memory system works with agents like Cursor and Claude Code. It applies to any AI agent that can read and write files to maintain cross-session continuity.

How do I structure AI agent memory for cross-session recall?▼

Structure AI agent memory using a structured stack containing MEMORY.md, sessions, DECISIONS.md, context, and handoffs directories to keep history compact and compressible for recall.

What is the best way to automate memory handoffs between AI agents?▼

The best way to automate memory handoffs between AI agents is by enforcing a frontmatter blueprint and utilizing deterministic workflows via optional scripts and references to drive reproducible memory management.

Do I need hooks to maintain persistent memory for AI agents?▼

No, you do not need hooks to maintain persistent memory for AI agents. This approach provides a file-based memory protocol that requires no hooks or external services to function.

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