superforecaster

Name: superforecaster
Availability: InStock
Author: luisschmitzheadline

Compute probability estimates, confidence intervals, and scenario analyses for user questions.

23|2|Updated Feb 10, 2026

Search Tags:#probability #calibration #uncertainty #risk-assessment #scenario-analysis #superforecasting #forecasts

Ready to run

npx skills add https://github.com/luisschmitzheadline/VC-Skills.md --skill superforecaster-luisschmitzheadline

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: superforecaster
Source: https://github.com/luisschmitzheadline/VC-Skills.md/tree/main/knowledge_skills/investment_analysis/skillsmp-superforecaster
Command: npx skills add https://github.com/luisschmitzheadline/VC-Skills.md --skill superforecaster-luisschmitzheadline

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Generate well-calibrated probability estimates for uncertain questions by applying the science of superforecasting to structure judgment and quantify risk.

Core Features & Use Cases

Applies superforecasting principles to produce probability estimates, confidence intervals, and scenario analyses for a wide range of questions.
Adapts to different information availability and outputs (binary, numeric, timing) to support decision making and risk assessment.
Enables structured forecasting in planning, budgeting, and strategic analysis by highlighting key drivers and uncertainties.

Quick Start

Provide a calibrated probability forecast for a specified uncertain outcome using the superforecasting methodology.

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 business outcomes?▼

Calibrated probability estimates are generated by applying superforecasting principles to your question. You provide the context and desired output format, and the system computes well-calibrated probabilities, confidence intervals, and scenario analyses.

Can I generate scenario analyses and confidence intervals for risk assessment?▼

Scenario analyses and confidence intervals are supported as core outputs. The system adapts to varying information availability and risk profiles to deliver distributions and interpretable metrics for your risk assessment needs.

What inputs do I need to provide for superforecasting probability calculations?▼

Superforecasting probability calculations require an explicit input of your question, relevant context, and desired output format. Providing these elements allows the system to quantify risk and produce accurate distributions.

Does this forecasting approach work with varying data availability?▼

The forecasting approach is designed to adapt across domains with varying data availability. It structures judgment to quantify risk and supports decision making whether data is abundant or scarce.

What output formats are supported for probability forecasts?▼

Probability forecasts support binary, numeric, and timing outputs. You specify the desired output format in your input to receive distributions, confidence intervals, and scenario analyses.

When should I use structured forecasting for planning and budgeting?▼

Structured forecasting should be used for planning and budgeting when you need to highlight key drivers and uncertainties. It quantifies risk and supports strategic analysis by producing calibrated probability estimates.