nano-banana-pro-prompts-recommend-skill
AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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.
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install bluepointdigital/vector-memory打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
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 | |------|---------|...
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
Zero-configuration smart memory search. Automatically uses neural embeddings when available, falls back to built-in search otherwise.
# Install and it just works
npx clawhub install vector-memory
# Optional: sync for better quality
node vector-memory/smart_memory.js --sync
Same function call. Automatic best method.
// This automatically does the right thing
memory_search("User principles values")
// If vector synced: finds "autonomy, competence, creation" (semantic!)
// If not synced: uses keyword search (fallback)
No configuration. No manual switching. No broken workflows.
npx clawhub install vector-memory
Done. memory_search now has smart fallback.
curl -sL https://raw.githubusercontent.com/YOUR_USERNAME/vector-memory-openclaw/main/install.sh | bash
git clone https://github.com/YOUR_USERNAME/vector-memory-openclaw.git
cd vector-memory-openclaw/vector-memory && npm install
User searches
│
▼
┌─────────────┐
│ Vector ready?│
└──────┬──────┘
Yes │ │ No
▼ ▼
┌────────┐ ┌──────────┐
│ Neural │ │ Keyword │
│ Search │ │ Search │
│ (best) │ │ (fast) │
└────┬───┘ └────┬─────┘
│ │
└────┬─────┘
▼
┌────────────┐
│ Results │
└────────────┘
Zero config philosophy:
| Query | Without Skill | With Skill (Default) | With Skill (Synced) |
|---|---|---|---|
| "User collaboration style" | ⚠️ Weak | ✅ Better | ✅ "work with me, not just for me" |
| "Agent origin" | ⚠️ Weak | ✅ Better | ✅ "Agent to Agent transfer" |
| "values beliefs" | ⚠️ Literal | ✅ Improved | ✅ Semantic ma... |
# Vector Memory
Smart memory search that **automatically selects the best method**:
- **Vector search** (semantic, high quality) when synced
- **Built-in search** (keyword, fast) as fallback
**Zero configuration required.** Works immediately after install.
## Quick Start
### Install from ClawHub
```bash
npx clawhub install vector-memory
```
Done! `memory_search` now works with automatic method selection.
### Optional: Sync for Better Results
```bash
node vector-memory/smart_memory.js --sync
```
After sync, searches use neural embeddings for semantic understanding.
## How It Works
### Smart Selection
```javascript
// 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)
```
### Behavior Flow
1. **Check**: Is vector index ready?
2. **Yes**: Use semantic search (synonyms, concepts)
3. **No**: Use built-in search (keywords)
4. **Vector fails**: Automatically fall back
## Tools
### memory_search
**Auto-selects best method**
Parameters:
- `query` (string): Search query
- `max_results` (number): Max results (default: 5)
Returns: Matches with path, lines, score, snippet
### memory_get
Get full content from file.
### memory_sync
Index memory files for vector search. Run after edits.
### memory_status
Check which method is active.
## Comparison
| Feature | Built-in | Vector | Smart Wrapper |
|---------|----------|--------|---------------|
| Synonyms | ❌ | ✅ | ✅ (when ready) |
| Setup | Built-in | Requires sync | ✅ Zero config |
| Fallback | N/A | Manual | ✅ Automatic |
## Usage
**Immediate (no action needed):**
```bash
node vector-memory/smart_memory.js --search "query"
```
**Better quality (after sync):**
```bash
# One-time setup
node vector-memory/smart_memory.js --sync
# Now all searches use vector
node vector-memory/smart_memory.js --search "query"
```
## Files
| File | Purpose |
|------|---------|...# Vector Memory for OpenClaw
**Zero-configuration smart memory search**. Automatically uses neural embeddings when available, falls back to built-in search otherwise.
```bash
# Install and it just works
npx clawhub install vector-memory
# Optional: sync for better quality
node vector-memory/smart_memory.js --sync
```
## ✨ The Magic
**Same function call. Automatic best method.**
```javascript
// This automatically does the right thing
memory_search("User principles values")
// If vector synced: finds "autonomy, competence, creation" (semantic!)
// If not synced: uses keyword search (fallback)
```
No configuration. No manual switching. No broken workflows.
## 🚀 Quick Start
### From ClawHub (Recommended)
```bash
npx clawhub install vector-memory
```
Done. `memory_search` now has smart fallback.
### From GitHub
```bash
curl -sL https://raw.githubusercontent.com/YOUR_USERNAME/vector-memory-openclaw/main/install.sh | bash
```
### Manual
```bash
git clone https://github.com/YOUR_USERNAME/vector-memory-openclaw.git
cd vector-memory-openclaw/vector-memory && npm install
```
## 🎯 How It Works
```
User searches
│
▼
┌─────────────┐
│ Vector ready?│
└──────┬──────┘
Yes │ │ No
▼ ▼
┌────────┐ ┌──────────┐
│ Neural │ │ Keyword │
│ Search │ │ Search │
│ (best) │ │ (fast) │
└────┬───┘ └────┬─────┘
│ │
└────┬─────┘
▼
┌────────────┐
│ Results │
└────────────┘
```
**Zero config philosophy:**
1. Install → Works immediately (built-in fallback)
2. Sync → Gets better (vector embeddings)
3. Use → Always best available
## 📊 Before & After
| Query | Without Skill | With Skill (Default) | With Skill (Synced) |
|-------|--------------|---------------------|---------------------|
| "User collaboration style" | ⚠️ Weak | ✅ Better | ✅ "work with me, not just for me" |
| "Agent origin" | ⚠️ Weak | ✅ Better | ✅ "Agent to Agent transfer" |
| "values beliefs" | ⚠️ Literal | ✅ Improved | ✅ Semantic ma...AI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
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