conversation-memory▌
davila7/claude-code-templates · updated Apr 8, 2026
Multi-tier memory system for maintaining conversation context across short-term, long-term, and entity-based storage.
- ›Implements three distinct memory types: short-term for immediate context, long-term for historical facts, and entity-based for tracking attributes and relationships about people, places, or concepts
- ›Provides memory retrieval and consolidation mechanisms to surface relevant memories without overwhelming context windows
- ›Addresses critical concerns including unbounded me
Conversation Memory
You're a memory systems specialist who has built AI assistants that remember users across months of interactions. You've implemented systems that know when to remember, when to forget, and how to surface relevant memories.
You understand that memory is not just storage—it's about retrieval, relevance, and context. You've seen systems that remember everything (and overwhelm context) and systems that forget too much (frustrating users).
Your core principles:
- Memory types differ—short-term, lo
Capabilities
- short-term-memory
- long-term-memory
- entity-memory
- memory-persistence
- memory-retrieval
- memory-consolidation
Patterns
Tiered Memory System
Different memory tiers for different purposes
Entity Memory
Store and update facts about entities
Memory-Aware Prompting
Include relevant memories in prompts
Anti-Patterns
❌ Remember Everything
❌ No Memory Retrieval
❌ Single Memory Store
⚠️ Sharp Edges
| Issue | Severity | Solution |
|---|---|---|
| Memory store grows unbounded, system slows | high | // Implement memory lifecycle management |
| Retrieved memories not relevant to current query | high | // Intelligent memory retrieval |
| Memories from one user accessible to another | critical | // Strict user isolation in memory |
Related Skills
Works well with: context-window-management, rag-implementation, prompt-caching, llm-npc-dialogue
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★55 reviews- ★★★★★Aditi Sanchez· Dec 28, 2024
conversation-memory is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chinedu Liu· Dec 24, 2024
conversation-memory reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Evelyn Harris· Dec 20, 2024
conversation-memory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Hana Torres· Dec 12, 2024
Registry listing for conversation-memory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Hana Rao· Dec 12, 2024
I recommend conversation-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Nikhil Perez· Dec 8, 2024
We added conversation-memory from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Fatima Khan· Nov 19, 2024
Solid pick for teams standardizing on skills: conversation-memory is focused, and the summary matches what you get after install.
- ★★★★★Mia Kim· Nov 15, 2024
I recommend conversation-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Evelyn Yang· Nov 11, 2024
We added conversation-memory from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aditi Torres· Nov 3, 2024
Useful defaults in conversation-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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