A powerful financial intelligence tool to monitor non-traditional market signals like politician trades and government contracts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install quiver
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 quiver 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 Quiver Quantitative?
The Quiver Quantitative skill enables AI agents and developers to integrate alternative financial data sets directly into their automated workflows. By leveraging this Openclaw Skills component, users can gain programmatic access to insights into US Congress trading activity, corporate lobbying expenditures, and government contract awards. It provides a technical bridge to Quiver's vast database, turning opaque political and corporate actions into actionable JSON data for market analysis and research.
This tool is designed for developers who need to correlate political events with market volatility. By using Openclaw Skills like this one, researchers can build dashboards or automated alerts that trigger when specific politicians or corporate insiders make significant moves in the stock market.
Quiver Quantitative Use Cases
- Monitor stock transactions made by members of the US House and Senate in real-time.
- Analyze corporate lobbying trends for specific tickers to understand political influence.
- Track government contract awards to defense and technology firms to forecast revenue.
- Detect corporate insider trading patterns to gauge internal confidence in a company.
- Correlate political activity with market movements using automated Openclaw Skills scripts.
How Quiver Quantitative Works
- The user provides a Quiver Quantitative API token via environment variables to authenticate requests.
- The skill executes a Python script targeting a specific data endpoint such as congress, lobbying, or contracts.
- Optional flags are applied to filter the request by specific stock tickers or politician names.
- The script communicates with the Quiver API to fetch the most recent or historical records.
- Data is returned in a structured JSON format, allowing for seamless integration with other Openclaw Skills or data pipelines.
Quiver Quantitative Setup
To use this within the Openclaw Skills framework, follow these steps:
- Obtain an API token from Quiver Quantitative.
- Set the environment variable in your shell or configuration file:
export QUIVER_API_KEY='your_api_token_here'
- Ensure Python is installed in your environment to execute the underlying scripts.
- Run the query script using the desired subcommand:
# Example: Query Congress trading for a specific ticker
skills/quiver/scripts/query_quiver.py congress --ticker NVDA
Quiver Quantitative Data Schema & Taxonomy
The skill returns data as a JSON array of objects. The specific fields vary by endpoint but generally follow this structure:
| Field | Description |
|---|---|
| Ticker | The stock symbol associated with the transaction. |
| Representative | The name of the politician (for Congress data). |
| TransactionDate | The date the trade or contract was executed. |
| Amount | The monetary value or range of the transaction. |
| Transaction | Type of action (e.g., Purchase, Sale, or Contract Award). |
| Description | Contextual details regarding lobbying or contracts. |
Quiver Quantitative Advanced Features
- Multi-endpoint support covering Congress, Lobbying, Contracts, and Insider transactions.
- Granular filtering via command-line arguments for specific politicians or tickers.
- Piped output compatibility with tools like jq for advanced CLI data processing.
- Scalable architecture that fits into larger Openclaw Skills automation suites for financial monitoring.
SKILL.md
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