smithery/davila7

conversation-memory

Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory Use when: conversation memory, remember, memory persistence, long-term memory, chat history.

Installation

$ npx skills add smithery/davila7 --skill conversation-memory

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,773 B
  • docs SUMMARY.md 224 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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:

  1. 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