remember

Name: remember
Availability: InStock
Author: lklimek

Store and retrieve persistent memories with deduplication and project scoping.

Updated Mar 5, 2026

Search Tags:#context #learning #agent #memory #persistence #deduplication

Ready to run

npx skills add https://github.com/lklimek/memcan --skill remember-lklimek

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: remember
Source: https://github.com/lklimek/memcan/tree/main/skills/remember
Command: npx skills add https://github.com/lklimek/memcan --skill remember-lklimek

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps agents retain and recall information across sessions, preventing repetitive mistakes and building project context over time.

Core Features & Use Cases

Memory Storage: Saves key learnings, decisions, and preferences.
Deduplication: Prevents redundant entries by checking for similar memories.
Scoped Memories: Allows memories to be tagged with project-specific scopes.
Use Case: When an agent discovers a crucial detail about a project's configuration, it can use this skill to "remember" it, ensuring the information is available in future interactions without re-explanation.

Quick Start

Use the remember skill to save the following information about the project's database schema.

Frequently Asked Questions about remember

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

FAQPage Schema

How do I persist agent memory across different sessions?▼

To persist agent memory across sessions, you need a mechanism that stores and retrieves learnings outside the active context window. This skill enables agents to retain project context, user preferences, and decisions using dedicated storage and search tools.

What is automatic deduplication for AI agent memory?▼

Automatic deduplication for AI agent memory prevents redundant entries by checking for similar stored information before saving. This ensures persistent context remains concise and avoids duplicating lessons learned or user preferences across sessions.

How do I save and recall project-specific context for an AI agent?▼

You save and recall project-specific context by tagging memories with project-specific scopes during storage. Agents can then search these scoped memories to retrieve critical configuration details or decisions in future interactions.

Can I store user preferences and decisions made by my agent?▼

Yes, you can store user preferences and decisions made by your agent. The memory storage capability explicitly saves key learnings, user preferences, and decisions, ensuring this context is available for future interactions without requiring re-explanation.

Does agent memory persistence work without external dependencies?▼

Agent memory persistence using this skill works without external dependencies, relying solely on integrated MCP tools for deterministic task execution. It leverages add_memory, search, and count_memories tools to manage context retention natively.