Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
FRED Navigator finds and retrieves economic data from the Federal Reserve Economic Data (FRED) database. It accepts a category ID, series ID, or natural-language query and returns matching series with metadata like frequency, units, and latest values. Natural-language queries go through intent recognition and two-stage validation before results are returned.
The two-stage validation (structural existence check plus semantic relevance scoring) reduces false matches when natural-language queries are ambiguous, which plain FRED search does not do.
When to use it
- Looking up the current federal funds rate series by name
- Browsing all series under a specific FRED category by ID
- Searching for unemployment data using plain English
- Retrieving metadata and recent values for a known series like CPIAUCSL
- Exploring child categories within a FRED topic hierarchy
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: find me inflation expectations data
- 1Interprets query intent and selects best-matching FRED category candidate
- 2Checks candidate exists in fred_categories_tree.json and has at least one series via scripts/fred_query.py check-category
- 3Runs semantic comparison between query and candidate name/path, scores relevance
- 4Accepts category if both checks pass, otherwise returns top-5 candidates for user selection
- 5Retrieves series list via scripts/fred_query.py category <id> and returns id, title, frequency, units, and latest value
List of inflation expectations series with metadata including frequency, units, seasonal adjustment, and last updated date
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.