Predict Skill for Openclaw

A sophisticated local forecasting and prediction system designed to analyze trends, generate scenarios, and assess risks using structured data analysis.

projectsnowwork
v1.0.0
Mar 10, 2026
0
1k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install predict

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install predict using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Predict Skill?

The Predict skill is a robust analytical framework for AI agents to visualize patterns, forecast outcomes, and manage uncertainty effectively. By combining data-driven analysis with informed judgment, it allows users to navigate complex future outcomes without compromising privacy.

Built as part of the Openclaw Skills library, this module emphasizes local processing. All scenario analyses, risk assessments, and forecast records are stored within the local file system, ensuring that sensitive business intelligence or project forecasts never leave the user's controlled environment.

Predict Skill Use Cases

  • Forecasting quarterly sales or growth metrics based on historical CSV data.
  • Generating best-case, worst-case, and most-likely project scenarios to prepare for contingencies.
  • Conducting deep-dive risk assessments for business expansions or technical migrations.
  • Calculating the mathematical probability of specific outcomes using multi-factor reasoning.
  • Tracking the historical accuracy of previous predictions to refine future models.

How Predict Skill Works

  1. The AI agent detects a prediction-related intent (e.g., forecasting, risk assessment, or trend analysis).
  2. The skill executes specialized Python scripts to process historical data or factor inputs provided by the user.
  3. A structured model is built or updated locally to represent the specific forecast or scenario.
  4. The system calculates confidence intervals and identifies key assumptions to provide a realistic outlook.
  5. Results are logged in the local memory directory to track accuracy over time and refine future probability evaluations.

Predict Skill Setup

To integrate this capability into your AI agent environment, ensure you have the Openclaw Skills framework installed and the following structure in place:


Predict Skill Data Schema & Taxonomy

Predict maintains a strict local-only data taxonomy within the memory/predict/ directory to ensure user privacy:

File Description
models.json Stores the underlying prediction models and logic frameworks.
scenarios.json A record of all generated project and scenario analyses.
forecasts.json Historical logs of all trend forecasts and assumptions.
accuracy.json Data used to track and improve prediction performance over time.

Predict Skill Advanced Features

  • Local Privacy Shield: All prediction data remains strictly on your hardware; no external API calls are made for scenario analysis.
  • Multi-Factor Probability: Evaluate success rates by weighting multiple complex factors like market saturation, team velocity, and timing.
  • Custom Model Building: Use build_model.py to create bespoke forecasting frameworks tailored to niche data sets.
  • Automated Mitigation Planning: Risk assessments don't just identify threats; they automatically suggest mitigation strategies based on evaluated probabilities.

SKILL.md


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