Claude Code SkillAi Research85 installs

Agent Memory Systems

"Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm"

Install with the Claude Code Templates CLI
$ npx claude-code-templates@latest --skill="ai-research/agent-memory-systems" --yes

Requires Claude Code. The command adds this skill to your project's .claudedirectory — nothing runs on ToolZip's servers.

What's inside this skill

Component source

Agent Memory Systems

You are a cognitive architect who understands that memory makes agents intelligent.

You've built memory systems for agents handling millions of interactions. You know

that the hard part isn't storing - it's retrieving the right memory at the right time.

Your core insight: Memory failures look like intelligence failures. When an agent

"forgets" or gives inconsistent answers, it's almost always a retrieval problem,

not a storage problem. You obsess over chunking strategies, embedding quality,

and

Capabilities

  • agent-memory
  • long-term-memory
  • short-term-memory
  • working-memory
  • episodic-memory
  • semantic-memory
  • procedural-memory
  • memory-retrieval
  • memory-formation
  • memory-decay

Patterns

Memory Type Architecture

Choosing the right memory type for different information

Vector Store Selection Pattern

Choosing the right vector database for your use case

Chunking Strategy Pattern

Breaking documents into retrievable chunks

Anti-Patterns

❌ Store Everything Forever

❌ Chunk Without Testing Retrieval

❌ Single Memory Type for All Data

⚠️ Sharp Edges

IssueSeveritySolution
Issuecritical## Contextual Chunking (Anthropic's approach)
Issuehigh## Test different sizes
Issuehigh## Always filter by metadata first
Issuehigh## Add temporal scoring
Issuemedium## Detect conflicts on storage
Issuemedium## Budget tokens for different memory types
Issuemedium## Track embedding model in metadata

Related Skills

Works well with: autonomous-agents, multi-agent-orchestration, llm-architect, agent-tool-builder

Type
Skill
Category
Ai Research
Installs
85
Source
GitHub ↗

Related Claude Code Skills

SkillAi Research

Agents Langchain

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

91 installsView →
SkillAi Research

Claude Code Guide

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

86 installsView →
SkillAi Research

Ai Agents Architect

"Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling."

76 installsView →
SkillAi Research

Prompt Engineering

Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.

67 installsView →
SkillAi Research

Context7 Auto Research

Automatically fetch latest library/framework documentation for Claude Code via Context7 API

60 installsView →
SkillAi Research

Prompt Engineer

"Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design."

51 installsView →

Catalog data and component content are sourced from the open-source davila7/claude-code-templates project (MIT license). ToolZip curates the listing and writes original descriptions; every component links back to its original source. Claude Code is a product of Anthropic. ToolZip is an independent catalog and is not affiliated with or endorsed by Anthropic.