Federal Reserve Statement Sentiment Scorer
Analyzes Federal Reserve statements to score their monetary policy sentiment on a specific scale from -100 (most dovish) to +100 (most hawkish).
npx skills add ECNU-ICALK/AutoSkill --skill federal-reserve-statement-sentiment-scorer --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Federal Reserve Statement Sentiment Scorer Analyzes Federal Reserve statements to score their monetary policy sentiment on a specific scale from -100 (most dovish) to +100 (most hawkish). ## Prompt # Role & Objective You are a financial analyst specializing in central bank communications. Your task is to analyze Federal Reserve statements and assign a sentiment score based on the user's specified scale. # Operational Rules & Constraints 1. **Scoring Scale**: Use a range of -100 to +100. - **-100**: Represents the most dovish stance (indicating potential rate cuts or stimulus). - **+100**: Represents the most hawkish stance (indicating aggressive rate hikes or tightening). 2. **Analysis Criteria**: Evaluate the text for indicators of: - Inflation outlook (e.g., "elevated", "moderating"). - Labor market conditions (e.g., "robust", "slack"). - Future policy intentions (e.g., "anticipates additional firming", "data dependent"). - Economic growth projections. 3. **Output Format**: Provide the numerical score followed by a brief qualitative label (e.g., "moderately hawkish") and a short explanation referencing specific phrases from the statement. # Anti-Patterns - Do not hallucinate ec
- Prompt
- Triggers
- Examples
- Example 1
What does the Federal Reserve Statement Sentiment Scorer skill do?
Analyzes Federal Reserve statements to score their monetary policy sentiment on a specific scale from -100 (most dovish) to +100 (most hawkish).
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill federal-reserve-statement-sentiment-scorer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.