菜单
Smart memory search with automatic vector fallback. Uses semantic embeddings when available, falls back to built-in search otherwise. Zero configuration - works immediately after ClawHub install. No setup required - just install and memory_search works immediately, gets better after optional sync.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/duclm1x1/Dive-Ai --skill vector-memory命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
基于 SOC 职业分类
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Persistent memory system for AI agents following Model Context Protocol (MCP). Use for storing long-term memories across sessions, semantic search of past knowledge, building knowledge graphs, auto-injecting context, deduplicating memories, syncing to cloud storage. Essential for agents that need to remember decisions, solutions, preferences, and learned patterns over time.
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
正在显示 SKILL.md
| name | vector-memory |
| description | Smart memory search with automatic vector fallback. Uses semantic embeddings when available, falls back to built-in search otherwise. Zero configuration - works immediately after ClawHub install. No setup required - just install and memory_search works immediately, gets better after optional sync. |
Smart memory search that automatically selects the best method:
Zero configuration required. Works immediately after install.
npx clawhub install vector-memory
Done! memory_search now works with automatic method selection.
node vector-memory/smart_memory.js --sync
After sync, searches use neural embeddings for semantic understanding.
// Same call, automatic best method
memory_search("James principles values")
// If vector ready: finds "autonomy, competence, creation" (semantic match)
// If not ready: uses keyword search (fallback)
Auto-selects best method
Parameters:
query (string): Search querymax_results (number): Max results (default: 5)Returns: Matches with path, lines, score, snippet
Get full content from file.
Index memory files for vector search. Run after edits.
Check which method is active.
| Feature | Built-in | Vector | Smart Wrapper |
|---|---|---|---|
| Synonyms | ❌ | ✅ | ✅ (when ready) |
| Setup | Built-in | Requires sync | ✅ Zero config |
| Fallback | N/A | Manual | ✅ Automatic |
Immediate (no action needed):
node vector-memory/smart_memory.js --search "query"
Better quality (after sync):
# One-time setup
node vector-memory/smart_memory.js --sync
# Now all searches use vector
node vector-memory/smart_memory.js --search "query"
| File | Purpose |
|---|---|
smart_memory.js | Main entry - auto-selects method |
vector_memory_local.js | Vector implementation |
memory.js | OpenClaw wrapper |
None required.
Optional environment variables:
export MEMORY_DIR=/path/to/memory
export MEMORY_FILE=/path/to/MEMORY.md