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memory

Store, recall, and forget key-value memories across sessions using JSON.

1|Updated Feb 25, 2026
Search Tags:#context#recall#memory#persistence#storage#key-value#forget
One-click install
npx skills add https://github.com/winsorllc/upgraded-carnival --skill memory-winsorllc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory
Source: https://github.com/winsorllc/upgraded-carnival/tree/main/.pi/skills/memory
Command: npx skills add https://github.com/winsorllc/upgraded-carnival --skill memory-winsorllc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This Skill provides a persistent key-value store for the agent, allowing it to remember information across different conversation sessions.

Core Features & Use Cases

  • Store: Save facts, preferences, or context.
  • Recall: Retrieve stored information.
  • Forget: Remove specific information or clear memory.
  • Categorization: Organize memories into logical groups (e.g., personal, work).
  • Use Case: "Remember that my project deadline is next Friday" or "What did I tell you about my client's preferences?"

Quick Start

Store the key "favorite_color" with the value "blue" by running the command: memory.sh store favorite_color blue

Frequently Asked Questions about memory

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

FAQPage Schema
How do I implement persistent memory for an agent across conversation sessions?▼

Persistent agent memory enables recall of information across different conversation sessions by storing data in a JSON file. This allows the agent to remember user preferences, project details, and context without losing data when a session ends.

How do I store and retrieve key-value context for an AI agent?▼

You store and retrieve agent context by using bash scripts with Python to manage a key-value storage system. Run commands to save specific keys and values, categorize them into logical groups, and recall them later during conversations.

Does this persistent memory storage require a specific runtime environment?▼

Yes, this persistent memory storage requires Python 3 to operate. The core operations utilize bash scripts executing Python commands to manage the JSON file where the categorized key-value data is physically saved.

How can I clear or forget specific information saved in an agent's memory?▼

You can forget specific information by using the forget command to remove targeted keys or clear the entire memory store. This manages the stored context by deleting obsolete facts, preferences, or categorized data from the JSON file.

What is the best way to categorize conversation context for an agent?▼

The best way to categorize conversation context is by organizing memories into logical groups such as personal or work. This persistent storage approach separates different project details and preferences within the JSON file for accurate retrieval.

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