predict

Forecast target outcomes with probability, horizons, and alternative scenarios.

4|1|Updated Jan 24, 2026

Search Tags:#uncertainty #time-series #data-analysis #forecast #predict #risk

Ready to run

npx skills add https://github.com/synaptiai/agent-capability-standard --skill predict

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: predict
Source: https://github.com/synaptiai/agent-capability-standard/tree/main/skills/predict
Command: npx skills add https://github.com/synaptiai/agent-capability-standard --skill predict

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Forecasting future states or outcomes from current data and patterns to inform decisions and manage uncertainty.

Core Features & Use Cases

Predict target outcomes with probability estimates.
Provide explicit horizons, alternative scenarios, and confidence levels.
Ground predictions with evidence anchors and provenance to support auditable decisions.

Quick Start

Ask the system to forecast a specific target over a defined horizon using your historical data and stated assumptions.

Frequently Asked Questions about predict

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

FAQPage Schema

How do I forecast future outcomes from historical data and manage uncertainty?▼

You can forecast future outcomes by providing historical data and stated assumptions to predict target states over a defined horizon, generating probability estimates to manage uncertainty in your data analysis.

What is the best way to predict risk scenarios for project planning?▼

Predicting risk scenarios involves applying assumed conditions to historical patterns to generate a trajectory of future states, explicitly outlining confidence levels and invalidation conditions for project planning decisions.

How do I structure a time-series forecast to include confidence levels and alternatives?▼

You structure a time-series forecast by defining a target over a specific horizon, which yields a structured output containing the prediction, probability, confidence levels, alternatives, and invalidation conditions.

Does predictive data analysis work without integrating external components or dependencies?▼

Yes, predictive data analysis works without external dependencies, using your current state inputs and historical patterns to generate system behavior forecasts and evidence anchors directly.

When should I not use automated forecasting for system behavior analysis?▼

Avoid automated forecasting when you lack historical patterns or defined horizons, because generating valid trajectory predictions requires current states and assumed conditions to establish evidence anchors.

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