memory-recall

Retrieve prior interaction data from markdown episode files for contextual responses.

2|Updated May 3, 2026
One-click install
npx skills add https://github.com/lukeivers/loam --skill memory-recall-lukeivers
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: memory-recall
Source: https://github.com/lukeivers/loam/tree/main/plugins/loam-skills/skills/memory-recall
Command: npx skills add https://github.com/lukeivers/loam --skill memory-recall-lukeivers

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill enables the AI to recall prior-session information stored on disk, ensuring continuity and consistency in multi-turn interactions.

Core Features & Use Cases

  • Prior Context Retrieval: Reads markdown episode files before responding to maintain dialogue coherence.
  • Search & Relevance: Uses file-based memory indexing to identify relevant past interactions for accurate recall.
  • Use Case: When a user asks about a previous decision or discussion topic, this Skill fetches and cites past details to inform the current response.

Quick Start

Ask the AI to recall earlier conversations or decisions related to a specific topic or entity.

Frequently Asked Questions about memory-recall

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

FAQPage Schema
How do I maintain context across multiple AI chat sessions?

To maintain context across multiple AI chat sessions, this Skill retrieves prior interaction data stored in markdown episode files and structured memory indexes from disk to inform ongoing dialogue.

How does AI recall previous decisions during a conversation?

AI recall of previous decisions works through file-based memory indexing that searches past interaction data on disk, fetching and citing specific details to maintain dialogue coherence in the current session.

Can I use markdown files for persistent memory in AI interactions?

Yes, you can use markdown files for persistent memory because this Skill accesses stored markdown episode files on disk to ensure continuity and consistency in multi-turn interactions without external databases.

What is the best way to retrieve prior context for complex projects?

The best way to retrieve prior context for complex projects is using search-based recall across markdown episode files and structured memory indexes, which identifies relevant past interactions to enhance multi-session continuity.

When do I need persistent memory stores for AI assistants?

You need persistent memory stores for AI assistants when managing complex projects and ongoing discussions that span multiple sessions, requiring reliable access to prior decisions and dialogue history stored on disk.