conversation-memory▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
Persistent memory systems for LLM conversations with tiered storage and intelligent retrieval.
- ›Implements three memory types: short-term (immediate context), long-term (historical facts), and entity-based (facts about specific entities)
- ›Provides memory retrieval and consolidation capabilities to surface relevant memories without overwhelming context windows
- ›Addresses critical concerns including unbounded memory growth, retrieval relevance, and strict user isolation to prevent cross-u
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
When to Use
This skill is applicable to execute the workflow or actions described in the overview.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★68 reviews- ★★★★★Dhruvi Jain· Dec 24, 2024
I recommend conversation-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Emma Gupta· Dec 16, 2024
Keeps context tight: conversation-memory is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Emma Smith· Dec 16, 2024
Useful defaults in conversation-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mia Sharma· Dec 12, 2024
Registry listing for conversation-memory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Omar Smith· Dec 8, 2024
I recommend conversation-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sophia Jackson· Dec 4, 2024
conversation-memory has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Soo Harris· Nov 27, 2024
Useful defaults in conversation-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Omar Johnson· Nov 23, 2024
conversation-memory reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Oshnikdeep· Nov 15, 2024
Useful defaults in conversation-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Lucas Bansal· Nov 7, 2024
conversation-memory is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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