Verified:GitHub

remember

Capture reusable insights and update conversational threads in a persistent knowledge store.

11|Updated Feb 6, 2026

Search Tags:#insight management #knowledge capture #context preservation #session summary #conversational threads #preference tracking

Ready to run

npx skills add https://github.com/anticorrelator/lore --skill remember-anticorrelator

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill ensures that valuable insights and evolving conversational threads are systematically captured and organized, preventing knowledge loss and maintaining context across sessions.

Core Features & Use Cases

Knowledge Capture: Identifies and stores reusable, non-obvious insights from conversations.
Thread Management: Updates existing conversational threads or creates new ones for significant topics.
Contextual Filtering: Allows capture constraints to focus on specific topics or exclude certain types of information.
Use Case: After a complex debugging session, use this Skill to automatically save the root cause, the workaround, and any new patterns discovered, ensuring that knowledge is retained for future reference and that the ongoing discussion about a specific feature is updated.

Quick Start

Run the remember skill to capture current insights and update threads.

Frequently Asked Questions about remember

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

FAQPage Schema

How do I preserve context and capture insights across different conversation sessions?▼

To preserve context and capture insights across sessions, you can scan conversation context for reusable, non-obvious insights and store them in a persistent knowledge store. This prevents knowledge loss by systematically organizing valuable information.

What is the best way to update conversational threads with new discussion topics?▼

Updating conversational threads is best handled by managing thread entries within a thread directory. This approach creates new files for significant topics or updates existing ones based on observed user preferences and discussion context.

How does knowledge capture handle noisy or irrelevant conversation data?▼

Knowledge capture handles irrelevant data by applying user-defined constraints to filter candidates. It specifically scans for reusable, stable, and high-confidence insights, ensuring only non-obvious information is stored in the knowledge base.

Can I use conversational thread management for complex debugging sessions?▼

Yes, you can use conversational thread management for complex debugging sessions. It automatically saves root causes, workarounds, and discovered patterns into a persistent knowledge store for future reference and ongoing feature discussion updates.

How do I organize captured insights by specific feature discussions?▼

Organizing captured insights by specific feature discussions is achieved by integrating a knowledge base with a thread directory. This system updates existing threads or creates new files based on discussion topics and observed user preferences.