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memory

Store and inject persistent user preferences and technical constraints across sessions.

Updated Feb 1, 2026
Search Tags:#learning#memory#rules#preferences#persistent#context-injection
One-click install
npx skills add https://github.com/twofoldtech-dakota/studio --skill memory-twofoldtech-dakota
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory
Source: https://github.com/twofoldtech-dakota/studio/tree/main/playbooks/memory
Command: npx skills add https://github.com/twofoldtech-dakota/studio --skill memory-twofoldtech-dakota

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Memory eliminates the need to re-teach STUDIO user preferences and project constraints between sessions by storing rules and conventions in a lightweight, file-based system.

Core Features & Use Cases

  • Persistent rule storage remembers user preferences, project conventions, and technical constraints across tasks.
  • Context injection reads global and domain-specific rules and injects them into the agent's working context.
  • Learning loop detects feedback-driven changes and writes updates to domain rule files for future tasks.
  • Real-world use case: when a team defines frontend styling conventions, Memory ensures frontend tasks remember and apply them without reconfiguration.

Quick Start

Invoke the memory skill to load global and domain rules into the agent context and begin planning with persistent preferences.

Frequently Asked Questions about memory

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

FAQPage Schema
How do I maintain persistent user preferences across sessions?▼

Persistent user preferences are maintained across sessions by storing rules and conventions in a lightweight, file-based system that injects context into the agent during tasks.

How does context injection work for project conventions?▼

Context injection works by reading global and domain-specific rules from a file-based memory store and loading them directly into the agent's working context before planning begins.

Can I use a learning loop to remember technical constraints automatically?▼

Yes, a learning loop detects feedback-driven changes during execution and writes updates to domain rule files, automatically remembering technical constraints for future tasks.

What is the best way to apply frontend styling conventions without reconfiguration?▼

The best way to apply frontend styling conventions without reconfiguration is using persistent rule storage, which ensures tasks remember and automatically apply defined constraints.

Do I need external dependencies to store domain-specific rules for STUDIO tasks?▼

No external dependencies are needed to store domain-specific rules for STUDIO tasks; the system uses a lightweight, file-based memory store and built-in scripts for persistence.

What are the limitations of a file-based memory store for persistent rules?▼

A file-based memory store provides lightweight persistence for global and domain rules but is limited to basic two-operation learning loops without complex database infrastructure.

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