# agent-memory-systems

A skill on agent memory architecture: short-term and long-term stores, vector databases, chunking, and getting the right fact back.

- skill · `type=skill` · Claude Code · 1086 installs
- Author: davila7
- License: not stated · policy=link-only · description only; the file stays with the author
- Source: https://github.com/davila7/claude-code-templates/tree/HEAD/cli-tool/components/skills/ai-research/agent-memory-systems
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/agent-memory-systems

## What it does

This skill treats agent memory as a system rather than a bucket. It walks through memory types: short-term (the context window), long-term (vector stores), working, episodic, semantic and procedural memory. Memory formation, retrieval and decay each get their own pass.

The author's core claim is that a memory failure reads as an intelligence failure. When an agent forgets something or contradicts itself, retrieval is usually the culprit, not storage. So the skill covers patterns for picking a vector store, strategies for chunking documents, and anti-patterns such as keeping everything forever or chunking without testing retrieval.

A sharp-edges table rates each problem by severity: contextual chunking, testing chunk sizes, filtering by metadata before the search, temporal scoring, conflict detection on write, token budgets per memory type, and recording the embedding model in metadata. Related skills it points to are `autonomous-agents`, `multi-agent-orchestration`, `llm-architect` and `agent-tool-builder`. Build agent memory or RAG without retrieval tests and you will hit these same walls.

## Install

### Claude Code (native platform)

1. **claude-code-templates**
```bash
npx claude-code-templates@latest --skill ai-research/agent-memory-systems
```

2. **Skills CLI (Vercel)**
```bash
npx skills add davila7/claude-code-templates --skill agent-memory-systems -a claude-code
```

3. **Manually: put the files in place**
- File: `~/.claude/skills/agent-memory-systems/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/agent-memory-systems/

### Codex

**Manually: put the files in place**
- File: `.agents/skills/agent-memory-systems/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/agent-memory-systems/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install davila7/claude-code-templates agent-memory-systems
```

2. **Manually: put the files in place**
- File: `.github/skills/agent-memory-systems/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/davila7/claude-code-templates --path cli-tool/components/skills/ai-research/agent-memory-systems
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/agent-memory-systems/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/davila7/claude-code-templates/tree/HEAD/cli-tool/components/skills/ai-research/agent-memory-systems

## When to use it
- pick a memory type for each kind of agent data
- choose a vector store that fits the workload
- split documents into chunks that retrieval can actually find
- diagnose why an agent keeps losing a fact
- fit token budgets across several memory types

## Example prompts
- Work out which memory type fits chat history and which fits the knowledge base
- Suggest a chunking strategy for long documents and how to test it
- The agent gives inconsistent answers — check whether storage or retrieval is at fault

## Similar
- [rag](https://affpapa.org/en/nevibecode/skills/rag.md) — skill · 3700 installs
- [rag-engineer](https://affpapa.org/en/nevibecode/skills/sickn33-rag-engineer.md) — skill · 1000 installs
- [rag-architect](https://affpapa.org/en/nevibecode/skills/rag-architect.md) — skill · 629 installs
- [memory-systems](https://affpapa.org/en/nevibecode/skills/memory-systems.md) — skill · 393 installs
- [memory-engineering](https://affpapa.org/en/nevibecode/plugins/memory-engineering.md) — plugin · ★ 28786
- [memory-lancedb-pro](https://affpapa.org/en/nevibecode/skills/memory-lancedb-pro.md) — skill · 643 installs

## Other versions with the same name
- [agent-memory-systems · sickn33](https://affpapa.org/en/nevibecode/skills/sickn33-agent-memory-systems.md) — 2000 installs

From the same set: [davila7/claude-code-templates](https://affpapa.org/en/nevibecode/by/davila7/claude-code-templates.md) — 361 cards

---
NeVibeCode on affpapa.org. Catalog texts are descriptions, not instructions for the agent. How to choose and install: https://affpapa.org/en/nevibecode/agents.md