reflect

Persist learnings across sessions in structured markdown memory files.

68|13|Updated Aug 9, 2025

Search Tags:#ai memory #continuous learning #reflection #knowledge persistence #pattern capture #skill memory

Ready to run

npx skills add https://github.com/kriegcloud/beep-effect --skill reflect-kriegcloud

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/kriegcloud/beep-effect/tree/main/.repos/beep-effect/.agents/skills/reflect
Command: npx skills add https://github.com/kriegcloud/beep-effect --skill reflect-kriegcloud

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the issue of AI models starting each conversation from scratch, leading to repetitive corrections and forgotten learnings. It enables persistent knowledge accumulation across sessions.

Core Features & Use Cases

Persistent Learning: Stores corrections, rules, and approvals in skill-specific MEMORY.md files.
Contextual Recall: Automatically loads learned patterns when a relevant skill is activated.
Use Case: After correcting an AI's code style preference once, the AI remembers and applies it in all future interactions related to that skill, improving consistency and reducing manual oversight.

Quick Start

Use the reflect skill to capture the correction about using vi.fn() instead of jest.fn() for Vitest mocks.

Frequently Asked Questions about reflect

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

FAQPage Schema

How do I make an AI agent remember corrections across different conversations?▼

AI memory for continuous learning works by persisting corrections, rules, and approvals in skill-specific structured markdown files. This ensures knowledge accumulation across conversational sessions without starting from scratch each time.

What is the best way to stop an AI from forgetting my code style preferences?▼

To stop an AI from forgetting code style preferences, use a continuous learning approach that stores corrections in skill-specific memory files. When a relevant skill is activated, contextual recall automatically loads these learned patterns for consistent application.

Can I manually trigger knowledge persistence to save specific AI learnings?▼

Yes, you can manually trigger knowledge persistence using manual reflection commands for knowledge management. This allows you to explicitly capture and store specific corrections, rules, or approvals in structured markdown files.

How does contextual recall work when loading learned patterns in AI sessions?▼

Contextual recall works by automatically detecting the learning context and loading stored patterns when a relevant skill is activated. This ensures the AI applies previously captured knowledge without requiring you to repeat corrections in new sessions.

Does continuous learning for AI agents require a specific database or dependency?▼

Continuous learning for AI agents does not require a specific database or external dependency. The system stores persistent knowledge using structured markdown files, making it lightweight and easy to manage without additional database infrastructure.