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.
Read-only Kalshi prediction market integration. Use for viewing markets, checking portfolio positions, analyzing prediction opportunities, and finding high-payoff/high-certainty trades. Triggers on Kalshi, prediction markets, event contracts, or trading recommendations.
Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.
SkillHub CLI
skillhub install henrik-openclaw/kalshiExaminez la source et la compatibilité, puis suivez les étapes d’installation.
Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.
Read-only integration with Kalshi's prediction market API.
Install dependencies:
pip install requests cryptography
For portfolio access (RSA key signing required):
mkdir -p ~/.kalshi
mv ~/Downloads/your-key-file.txt ~/.kalshi/private_key.pem
chmod 600 ~/.kalshi/private_key.pem
~/.kalshi/credentials.json:{
"api_key_id": "your-key-id-here",
"private_key_path": "~/.kalshi/private_key.pem"
}
Or run interactive setup:
python scripts/kalshi_portfolio.py setup
# List trending markets
python scripts/kalshi_markets.py trending
# Search markets by query
python scripts/kalshi_markets.py search "bitcoin"
# Get specific market details
python scripts/kalshi_markets.py market TICKER
# Find high-value opportunities
python scripts/kalshi_markets.py opportunities
# View positions
python scripts/kalshi_portfolio.py positions
# View balance
python scripts/kalshi_portfolio.py balance
# Trade history
python scripts/kalshi_portfolio.py history
The opportunities command identifies markets where:
Formula: expected_value = probability * payoff - (1 - probability) * cost
A good opportunity...
Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.
# Kalshi Prediction Markets
Read-only integration with Kalshi's prediction market API.
## Capabilities
- **Browse markets**: List active events and markets by category
- **Market analysis**: Get prices, volumes, orderbook depth
- **Portfolio view**: Check positions and P&L (requires API key)
- **Trade recommendations**: Find high-certainty, high-payoff opportunities
## Setup
Install dependencies:
```bash
pip install requests cryptography
```
For portfolio access (RSA key signing required):
1. Go to [kalshi.com/account/profile](https://kalshi.com/account/profile)
2. Create new API key → save the **Key ID** and download the **private key**
3. Store credentials:
```bash
mkdir -p ~/.kalshi
mv ~/Downloads/your-key-file.txt ~/.kalshi/private_key.pem
chmod 600 ~/.kalshi/private_key.pem
```
4. Create `~/.kalshi/credentials.json`:
```json
{
"api_key_id": "your-key-id-here",
"private_key_path": "~/.kalshi/private_key.pem"
}
```
Or run interactive setup:
```bash
python scripts/kalshi_portfolio.py setup
```
## Scripts
### Market Data (No Auth Required)
```bash
# List trending markets
python scripts/kalshi_markets.py trending
# Search markets by query
python scripts/kalshi_markets.py search "bitcoin"
# Get specific market details
python scripts/kalshi_markets.py market TICKER
# Find high-value opportunities
python scripts/kalshi_markets.py opportunities
```
### Portfolio (Auth Required)
```bash
# View positions
python scripts/kalshi_portfolio.py positions
# View balance
python scripts/kalshi_portfolio.py balance
# Trade history
python scripts/kalshi_portfolio.py history
```
## Opportunity Analysis
The `opportunities` command identifies markets where:
- **High certainty**: Price ≥85¢ YES or ≤15¢ YES (implies 85%+ confidence)
- **Meaningful payoff**: Potential return ≥10% on capital
- **Sufficient liquidity**: Orderbook depth supports reasonable position size
Formula: `expected_value = probability * payoff - (1 - probability) * cost`
A good opportunity...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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