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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

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claude-code-templates
33k200 skills200 agents200 commands2 MCP

Claude Code

$ npx -y skills add davila7/claude-code-templates --skill agent-memory-systems --agent claude-code

SKILL.md

agent-memory-systems.SKILL.md
name: agent-memory-systems
description: "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"
metadata:
  source: vibeship-spawner-skills (Apache 2.0)

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

| Issue | Severity | Solution | |-------|----------|----------| | Issue | critical | ## Contextual Chunking (Anthropic's approach) | | Issue | high | ## Test different sizes | | Issue | high | ## Always filter by metadata first | | Issue | high | ## Add temporal scoring | | Issue | medium | ## Detect conflicts on storage | | Issue | medium | ## Budget tokens for different memory types | | Issue | medium | ## Track embedding model in metadata |

Related Skills

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

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Questions about agent-memory-systems.

Which coding agents can use agent-memory-systems?
agent-memory-systems installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.