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.
Hybrid memory strategy combining OpenClaw's built-in vector memory with Graphiti temporal knowledge graph. Use when you need to recall past context, answer temporal questions ("when did X happen?"), or search memory files. Provides decision framework for when to use memory_search vs Graphiti.
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 clawdbrunner/hybrid-memoryInspect 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.
Two memory systems, each with different strengths. Use both.
| Question Type | Tool | Example |
|---|---|---|
| Document content | memory_search |
"What's in GOALS.md?" |
| Curated notes | memory_search |
"What are our project guidelines?" |
| Temporal facts | Graphiti | "When did we set up Slack?" |
| Conversations | Graphiti | "What did the user say last Tuesday?" |
| Entity tracking | Graphiti | "What projects involve Alice?" |
Semantic search over markdown files (MEMORY.md, memory/**/*.md).
memory_search query="your question"
Then use memory_get to read specific lines if needed.
Search for facts with time awareness:
graphiti-search.sh "your question" GROUP_ID 10
Log important facts:
graphiti-log.sh GROUP_ID user "Name" "Fact to remember"
Common group IDs:
main-agent — Primary agentuser-personal — User's personal contextWhen answering questions about past context:
memory_search
Add to your AGENTS.md:
### Memory Recall (Hybrid)
**Temporal questions** ("when?", "what changed?", "last Tuesday"):
```bash
graphiti-search.sh "query" main-agent 10
Document questions ("what's in X?", "find notes about Y"):
memory_search query="your query"
When answering past context: check Graphiti for temporal, memory_search for docs.
## Setup
Full setup guide: https://github.com/clawdbrunner/openclaw-graphiti-memory
**Part 1: OpenClaw Memory** — Configure embedding provider (Gemini recommended)
**Part 2: Graphiti** — Deploy Docker stack, install sync daemons
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Hybrid Memory System
Two memory systems, each with different strengths. Use both.
## When to Use Which
| Question Type | Tool | Example |
|--------------|------|---------|
| Document content | `memory_search` | "What's in GOALS.md?" |
| Curated notes | `memory_search` | "What are our project guidelines?" |
| Temporal facts | Graphiti | "When did we set up Slack?" |
| Conversations | Graphiti | "What did the user say last Tuesday?" |
| Entity tracking | Graphiti | "What projects involve Alice?" |
## Quick Reference
### memory_search (Built-in)
Semantic search over markdown files (`MEMORY.md`, `memory/**/*.md`).
```
memory_search query="your question"
```
Then use `memory_get` to read specific lines if needed.
### Graphiti (Temporal)
Search for facts with time awareness:
```bash
graphiti-search.sh "your question" GROUP_ID 10
```
Log important facts:
```bash
graphiti-log.sh GROUP_ID user "Name" "Fact to remember"
```
Common group IDs:
- `main-agent` — Primary agent
- `user-personal` — User's personal context
## Recall Pattern
When answering questions about past context:
1. **Temporal questions** → Check Graphiti first
2. **Document questions** → Use `memory_search`
3. **Uncertain** → Try both, combine results
4. **Low confidence** → Say you checked but aren't sure
## AGENTS.md Template
Add to your AGENTS.md:
```markdown
### Memory Recall (Hybrid)
**Temporal questions** ("when?", "what changed?", "last Tuesday"):
```bash
graphiti-search.sh "query" main-agent 10
```
**Document questions** ("what's in X?", "find notes about Y"):
```
memory_search query="your query"
```
When answering past context: check Graphiti for temporal, memory_search for docs.
```
## Setup
Full setup guide: https://github.com/clawdbrunner/openclaw-graphiti-memory
**Part 1: OpenClaw Memory** — Configure embedding provider (Gemini recommended)
**Part 2: Graphiti** — Deploy Docker stack, install sync daemonsAI skill for OpenClaw & Claude Code — recommend from 10000+ Nano Banana Pro (Gemini) image prompts. Smart search by use case, content remix, sample images.
AI Agent Orchestrator with Skills System - Give AI Agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude, Codex or any AI Agent from one dashboard. Move Agents between c...
AI agent skills for the Universal Registry - search, chat, and register 72,000+ agents across 14+ protocols. Works with Claude, Codex, Cursor, OpenClaw, and any AI assistant.
A cross-platform skills manager for AI IDEs. Search marketplace, download locally, and install to Claude, Cursor, Windsurf, and more with one click.