An AI-powered economic analyst skill for tracking Federal Reserve policy, interest rates, and inflation data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install fed-agent
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 fed-agent 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 Fed Agent Skill?
The Fed Agent Skill acts as a specialized economic analyst designed to monitor and interpret Federal Reserve movements. By integrating directly into your workflow, this Openclaw Skills component provides real-time tracking of FOMC meetings, interest rate adjustments, and critical inflation metrics such as CPI and PCE. It streamlines the collection of official data and Chair speeches, transforming complex policy shifts into actionable insights for developers and financial analysts.
This skill is essential for anyone needing to maintain a pulse on the macro-economic landscape without manual data scraping. Whether you are building financial models or monitoring market triggers, the Fed Agent Skill ensures you have the most current Fed data delivered directly to your environment in a clean, structured format.
Fed Agent Skill Use Cases
- Monitoring FOMC meeting outcomes and voting records for policy shifts.
- Tracking inflation data including CPI and Core PCE for economic forecasting.
- Analyzing Federal Reserve Chair speeches and Dot Plot projections for future rate paths.
- Automating the collection of employment data and economic indicators.
- Generating structured markdown reports for internal economic briefings.
How Fed Agent Skill Works
- The skill initiates by polling official Federal Reserve and Bureau of Labor Statistics (BLS) data sources to retrieve the latest policy and economic information.
- It extracts specific factual indicators, including interest rate targets, inflation percentages, and policy statement nuances.
- The collected data is parsed and formatted into a structured markdown table or a machine-readable JSON object.
- The final output is delivered either directly to the chat interface or saved to a specified local file for further processing within the Openclaw Skills ecosystem.
Fed Agent Skill Setup
To get started with this skill, execute the following command in your terminal. Ensure you have the Openclaw environment configured correctly.
# Basic execution to print output directly to chat
python "scripts/track_fed_policy.py" --output-file ""
To include specific datasets like inflation or employment, use the following flags:
# Execution with inflation and employment data
python "scripts/track_fed_policy.py" --output-file "" --with-inflation --with-employment
Fed Agent Skill Data Schema & Taxonomy
The Fed Agent Skill organizes economic data into a structured format, primarily focusing on chronological and categorical metrics. The standard output schema includes the following fields:
| Field | Description | Source |
|---|---|---|
| Metric | The specific economic indicator (e.g., Fed Funds Rate, CPI) | BLS/FOMC |
| Value/Status | The current numerical value or policy stance | Official Release |
| Date/Time | Timestamp of the data release or scheduled event | Public Calendar |
| Source | The origin of the data (e.g., FOMC Statement, BLS Data) | Official API/Web |
For automation purposes, the output-mode json flag provides a nested object structure containing these fields as keys.
Fed Agent Skill Advanced Features
- JSON output mode for seamless integration with other Openclaw Skills and automated data pipelines.
- Conditional flags for granular data retrieval, such as inflation-specific or employment-specific datasets.
- Customizable polling intervals and API endpoint configuration via the core Python script.
- Support for saving outputs to persistent Markdown files for historical tracking and documentation.
- Multi-skill integration capabilities, allowing context sharing with geopolitical fetchers and market news tools.
SKILL.md
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