rfi
Crowdsourced forecasting questions and predictions from the RAND Forecasting Initiative (formerly INFER). Policy-relevant forecasting questions with crowd probabilities, individual forecaster predictions with rationales, and comments. Use for any question about geopolitics, national security, science and technology policy, or when you need calibrated crowd forecasts as base rates. All methods support cutoff_date for backtesting.
npx skills add majiayu000/claude-skill-registry --skill sdk-rfi --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.
# RAND Forecasting Initiative (RFI) SDK that provides access to the RAND Forecasting Initiative crowdsourced forecasting platform (formerly INFER, powered by Cultivate Labs). It covers policy-relevant forecasting questions with aggregated crowd probabilities and individual forecaster predictions with rationales. ## Quick Start ```python from sdk_rfi import Client client = Client() # Uses RFI_EMAIL and RFI_PASSWORD env vars ``` ## Key Methods | Method | What it does | |--------|-------------| | `client.questions.list(...)` | List forecasting questions with filtering by status, tags, challenges, date ranges | | `client.questions.get(question_id)` | Get a specific question with answers and crowd probabilities | | `client.prediction_sets.list(question_id=...)` | Get individual forecaster predictions with rationales for a question | | `client.comments.list(commentable_id=..., commentable_type=...)` | Get discussion comments on a question | ## Data Coverage - **Domain**: Politics / policy forecasting - **Countries/Regions**: Global (US policy focus) - **Time range**: Questions from ~2020 to present - **Update frequency**: Event-driven (new questions published, forecasts updated continuou
- Quick Start
- Key Methods
- Data Coverage
- Forecasting Patterns
- Common Queries
- Full Method Reference
What does the rfi skill do?
Crowdsourced forecasting questions and predictions from the RAND Forecasting Initiative (formerly INFER). Policy-relevant forecasting questions with crowd probabilities, individual forecaster predictions with rationales, and comments. Use for any question about geopolitics, national security, science and technology policy, or when you need calibrated crowd forecasts as base rates. All methods support cutoff_date for backtesting.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill sdk-rfi --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 majiayu000/claude-skill-registry, a repository with 534 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.