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v-memory

Save, index, and recall AI agent memories with memU integration.

26|3|Updated Jan 10, 2026
Search Tags:#recall#search#memory#persistence#AI memory#memU
One-click install
npx skills add https://github.com/kks0488/vibe-claude --skill v-memory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: v-memory
Source: https://github.com/kks0488/vibe-claude/tree/main/skills/v-memory
Command: npx skills add https://github.com/kks0488/vibe-claude --skill v-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a persistent memory system for AI agents by saving, indexing, and recalling knowledge with memU integration.

Core Features & Use Cases

  • Memory organization: Save and categorize memories as lessons, patterns, or decisions for quick retrieval.
  • Semantic search: Enables fast retrieval via memU-backed search and local lookup.
  • Use Case: Capture failed experiments, architectural choices, and reusable knowledge for rapid reuse in future tasks.

Quick Start

/v-memory save lesson "Example: failed API call" to store a failure context, then /v-memory search "API reliability" to retrieve related memories.

Frequently Asked Questions about v-memory

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement persistent memory for an AI agent to recall past interactions?▼

Persistent AI agent memory can be implemented by saving and indexing knowledge into categorized local storage. This allows agents to recall past lessons, patterns, and decisions during future tasks.

What is semantic search for AI memory and how does it retrieve past failures?▼

Semantic search for AI memory retrieves stored contexts by matching meaning rather than exact keywords. It enables fast recall of past failures and architectural decisions by querying related concepts.

How do I save and categorize architectural decisions for future AI tasks?▼

To save architectural decisions, use a categorized memory system to store contexts as lessons, patterns, or decisions. This organizes knowledge for quick retrieval and reuse in future tasks.

Do I need memU API access to use a persistent memory system for AI agents?▼

Yes, memU API access is required to enable semantic search and organized recall. The system also uses local storage at ~/.claude/.vibe/memory for saving and indexing knowledge.

What's the best way to capture reusable patterns and failed experiments in AI workflows?▼

The best way to capture reusable patterns and failed experiments is using a persistent memory system that categorizes knowledge. It saves failure contexts and architectural choices for rapid reuse.

Can I search local AI memory storage without relying entirely on external APIs?▼

Yes, the memory system supports local lookup at ~/.claude/.vibe/memory alongside memU-backed semantic search. This hybrid approach enables fast retrieval of indexed knowledge from local storage.

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