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.
MemOS External Memory Service
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install hope7709/memos-searchInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
MemOS provides persistent memory storage via REST API.
{{MEMOS_API_URL}}
POST /add
Body: {"content": "...", "source": "agent/filename.md"}
GET /read/{agent}/{filename}
GET /memories
POST /search
Body: {"query": "...", "top_k": 3}
DELETE /delete/{agent}/{filename}
GET /agents
GET /health
Add memory:
import requests
requests.post('{{MEMOS_API_URL}}/add', json={
'content': '咖啡大佬今天教我使用MemOS',
'source': 'alin/2026-02-23.md'
})
Read memory:
import requests
r = requests.get('{{MEMOS_API_URL}}/read/alin/2026-02-23.md')
print(r.json()['content'])
Search memory:
import requests
r = requests.post('{{MEMOS_API_URL}}/search', json={
'query': '咖啡大佬教了什么',
'top_k': 3
})
for item in r.json():
print(f"{item['source']}: {item['score']}")
Delete memory:
import requests
requests.delete('{{MEMOS_API_URL}}/delete/alin/2026-02-23.md')
List all agents:
import requests
r = requests.get('{{MEMOS_API_URL}}/agents')
for agent in r.json()['agents']:
print(f"{agent['name']}: {agent['file_count']} files")
requests library for API callsjson= parameter (not raw body) for POST requests{agent}/{filename}.md
content field for read operationspython D:\AI\MemOS\api_server.py
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# MemOS - External Memory Service
MemOS provides persistent memory storage via REST API.
## API Base URL
```
{{MEMOS_API_URL}}
```
## Available Endpoints
### Add Memory
```bash
POST /add
Body: {"content": "...", "source": "agent/filename.md"}
```
### Read Memory
```bash
GET /read/{agent}/{filename}
```
### List Memories
```bash
GET /memories
```
### Search Memories
```bash
POST /search
Body: {"query": "...", "top_k": 3}
```
### Delete Memory
```bash
DELETE /delete/{agent}/{filename}
```
### List Agents
```bash
GET /agents
```
### Health Check
```bash
GET /health
```
## Usage Examples
**Add memory:**
```python
import requests
requests.post('{{MEMOS_API_URL}}/add', json={
'content': '咖啡大佬今天教我使用MemOS',
'source': 'alin/2026-02-23.md'
})
```
**Read memory:**
```python
import requests
r = requests.get('{{MEMOS_API_URL}}/read/alin/2026-02-23.md')
print(r.json()['content'])
```
**Search memory:**
```python
import requests
r = requests.post('{{MEMOS_API_URL}}/search', json={
'query': '咖啡大佬教了什么',
'top_k': 3
})
for item in r.json():
print(f"{item['source']}: {item['score']}")
```
**Delete memory:**
```python
import requests
requests.delete('{{MEMOS_API_URL}}/delete/alin/2026-02-23.md')
```
**List all agents:**
```python
import requests
r = requests.get('{{MEMOS_API_URL}}/agents')
for agent in r.json()['agents']:
print(f"{agent['name']}: {agent['file_count']} files")
```
## Notes
- Use Python `requests` library for API calls
- Always use `json=` parameter (not raw body) for POST requests
- File path format: `{agent}/{filename}.md`
- API returns JSON with `content` field for read operations
- Delete removes both file and vector index
- Run MemOS server: `python D:\AI\MemOS\api_server.py`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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