Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Kalshi
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.
skill openclawclawhub Free
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.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- references/api.md, scripts/kalshi_portfolio.py, scripts/kalshi_markets.py, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.0
Provenance
- Publisher
- henrik-openclaw
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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: pip install requests cryptography For portfolio access (RSA key signing required): Go to kalshi.com/account/profile Create new API key β save the Key ID and download the private key Store credentials: mkdir -p ~/.kalshi mv ~/Downloads/your-key-file.txt ~/.kalshi/private_key.pem chmod 600 ~/.kalshi/private_key.pem Create ~/.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
Market Data (No Auth Required)
# 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)
# 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 β₯85Β’ YES or β€15Β’ YES (implies 85%+ confidence) Meaningful payoff: Potential return β₯10% on capital Sufficient liquidity: Orderbook depth supports reasonable position size Formula: expected_value = probability * payoff - (1 - probability) * cost A good opportunity has: EV / cost > 0.1 (10%+ expected return)
Categories
Kalshi markets span: Politics & Elections Economics (Fed rates, inflation, GDP) Weather & Climate Finance (stock prices, crypto) Entertainment & Sports Science & Tech
API Reference
See references/api.md for endpoint details.
Important Notes
This skill is READ-ONLY β no trade execution Public endpoints don't require authentication Portfolio/balance requires API credentials Markets settle in cents (100Β’ = $1) All times in UTC
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs2 Scripts
- SKILL.md
- references/api.md
- scripts/kalshi_markets.py
- scripts/kalshi_portfolio.py