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
npx skills add majiayu000/claude-skill-registry --skill agent-memory-systems-claude-code-communit-claude-code-resource-2 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 | critic
- Capabilities
- Patterns
- Memory Type Architecture
- Vector Store Selection Pattern
- Chunking Strategy Pattern
- Anti-Patterns
- ❌ Store Everything Forever
- ❌ Chunk Without Testing Retrieval
- ❌ Single Memory Type for All Data
- ⚠️ Sharp Edges
- Related Skills
What does the agent-memory-systems skill do?
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
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill agent-memory-systems-claude-code-communit-claude-code-resource-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.