A comprehensive interface for searching, analyzing, and executing trades on Manifold Markets prediction platforms.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install silk-manifold
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install silk-manifold using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Manifold Markets Prediction Trading?
This skill provides a robust bridge between AI agents and Manifold Markets, the world's largest social prediction market. By utilizing this integration within Openclaw Skills, developers and researchers can programmatically access real-time market probabilities, track global event sentiments, and manage virtual mana portfolios through a structured JSON interface.
The tool is designed for precision, allowing agents to filter markets by popularity, volume, or closing date. Whether you are building an automated trading bot or a research assistant that needs to quantify the likelihood of future events, this skill offers the necessary endpoints to turn prediction market data into actionable insights.
Manifold Markets Prediction Trading Use Cases
- Monitoring real-time probability shifts for political elections, tech releases, and economic indicators.
- Automating limit orders based on algorithmic triggers within the Openclaw Skills framework.
- Conducting deep dives into market sentiment via advanced search filters and sorting.
- Managing complex portfolios across multiple-choice and binary prediction markets.
- Simulating trading strategies using dry-run modes to validate agent logic without financial risk.
How Manifold Markets Prediction Trading Works
- The agent authenticates using a MANIFOLD_API_KEY provided in the environment configuration.
- Commands are issued via a Python-based CLI that interacts directly with the Manifold API.
- The skill retrieves market data, including contract IDs, slugs, and current probabilities, returning everything in clean JSON format.
- For trading actions, the agent can execute market orders or sophisticated limit orders with specific probability thresholds.
- Post-trade, the skill allows for detailed portfolio tracking and position analysis to measure performance over time.
Manifold Markets Prediction Trading Setup
To begin using this tool with Openclaw Skills, ensure you have Python 3 installed and follow these steps:
# Set your Manifold API key in your environment
export MANIFOLD_API_KEY='your_api_key_here'
# Verify your account balance and connection
python3 scripts/manifold.py balance
Ensure that your agent has access to the scripts/manifold.py path within your project directory.
Manifold Markets Prediction Trading Data Schema & Taxonomy
The skill organizes data around Markets and Bets, providing detailed metadata for every transaction.
| Attribute | Description |
|---|---|
| contract-id | The unique identifier for a market, required for betting and selling. |
| slug | The human-readable portion of the market URL used for quick lookups. |
| mana | The currency unit (M$) used for all transactions on the platform. |
| probability | A decimal representation (0.01 to 0.99) of the market's current odds. |
| answer-id | Required for interacting with specific options in multiple-choice markets. |
Manifold Markets Prediction Trading Advanced Features
- Dry-run capability to simulate bets and prevent unintended mana expenditure during Openclaw Skills development.
- Support for expiring limit orders with custom millisecond-based expiration timestamps.
- Multi-choice market integration allowing for specific answer targeting and share selling.
- Advanced sorting for research including daily-score, liquidity, and 24-hour-vol filters.
- Deep-link position tracking for specific user IDs or market leaderboards.
SKILL.md
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