skills.rest
Zurybr
ZurybrCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

learning-sdk-integration

Integrates persistent memory into LLM agents via a 3-line pattern for OpenAI, Anthropic, and Gemini.

Updated Feb 24, 2026
Search Tags:#integration#llm#sdk#memory#persistence#agentic
One-click install
npx skills add https://github.com/Zurybr/lefarma-skills --skill learning-sdk-integration
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: learning-sdk-integration
Source: https://github.com/Zurybr/lefarma-skills/tree/main/letta/learning-sdk
Command: npx skills add https://github.com/Zurybr/lefarma-skills --skill learning-sdk-integration

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of giving LLM agents persistent memory, allowing them to recall past interactions and context across sessions, thereby enhancing their capabilities and user experience.

Core Features & Use Cases

  • Universal Integration: Seamlessly integrates with OpenAI, Anthropic, Gemini, and other LLM providers using a simple 3-line pattern.
  • Persistent Memory: Enables agents to maintain conversation history and context across multiple interactions.
  • Use Case: Building a customer support chatbot that remembers previous customer issues and preferences to provide more personalized and efficient assistance.

Quick Start

Wrap your LLM SDK calls with the learning context manager to enable memory.

Frequently Asked Questions about learning-sdk-integration

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

FAQPage Schema
How do I add persistent memory to LLM agents?▼

Add persistent memory to LLM agents by wrapping your LLM SDK calls with a context manager, enabling conversation history persistence and context-aware capabilities across multiple sessions.

Can I use this memory integration with OpenAI, Anthropic, and Gemini providers?▼

Yes, this memory integration supports universal compatibility across OpenAI, Anthropic, and Gemini providers using a simple 3-line integration pattern for both synchronous and asynchronous SDK calls.

What is the best way to maintain conversation history in an agentic system?▼

The best way to maintain conversation history in an agentic system is using a learning SDK that wraps your LLM calls, allowing agents to recall past interactions and context across sessions.

Does integrating persistent memory require complex setup for multi-agent systems?▼

No, integrating persistent memory into multi-agent systems requires only a universal 3-line integration pattern to facilitate context-aware capabilities and conversation persistence across providers.

Why do LLM agents lose context across different sessions?▼

LLM agents lose context across different sessions because they lack persistent memory by default, which this SDK integration solves by maintaining conversation history and enabling recall of past interactions.

Do I need to rewrite my existing SDK calls to enable context-aware capabilities?▼

No, you do not need to rewrite existing SDK calls; you simply wrap your synchronous or asynchronous LLM SDK calls with the learning context manager to enable context-aware capabilities.

Related Skills

Explore More Software Engineering Skills→
hyperspellhyperspell
15

Setting up Hyperspell

Automate Hyperspell SDK setup, API key configuration, and memory ingestion.

Official
Intermediate
phuhao00phuhao00

ai-customer-service-skill

Build AI customer service conversations and personalized recommendations for the real_deal platform.

Community
Advanced
paxlabs-incpaxlabs-inc
7

hermes-agent

Configure and manage Hermes Agent instances across messaging platforms with persistent memory.

Community
Advanced
handsomelong922handsomelong922

chroma

Store and retrieve embeddings with metadata using a vector database.

Community
Intermediate