One-click install
npx skills add https://github.com/agentydragon/ducktape --skill superforecaster
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: superforecaster
Source: https://github.com/agentydragon/ducktape/tree/main/nix/home/claude_code/skills/superforecaster
Command: npx skills add https://github.com/agentydragon/ducktape --skill superforecaster

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Calibrate probability judgments in uncertain situations to improve decision-making by providing structured, evidence-based estimates rather than intuition alone.

Core Features & Use Cases

  • Calibration framework based on superforecasting principles applied to a range of questions
  • Question classification that adapts method to information availability and desired output
  • Output formats include probability estimates, confidence intervals, and scenario trajectories

Quick Start

Ask a probabilistic question in clear terms and the skill will return a calibrated forecast.

Frequently Asked Questions about superforecaster

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I get calibrated probability estimates for uncertain questions?

To get calibrated probability estimates, ask a clear probabilistic question and the skill applies superforecasting principles to return structured, evidence-based point estimates and confidence intervals.

What is superforecasting and how does it improve risk analysis?

Superforecasting improves risk analysis by replacing intuition alone with structured, evidence-based probability judgments and calibration frameworks, delivering measurable confidence intervals for uncertain scenarios.

Can I use probability forecasting for project planning and finance?

Yes, probability forecasting adapts its question classification method to various domains including project planning and finance, generating scenario trajectories based on available data.

What is the best way to quantify uncertainty in scenario planning?

The best way to quantify uncertainty in scenario planning is using calibrated forecasting methods that produce structured probability estimates, confidence intervals, and scenario trajectories rather than intuition.

What output formats can I expect from uncertainty calibration?

Uncertainty calibration outputs include probability point estimates, confidence intervals, and scenario trajectories, adapting to your desired output format and information availability.