model-tracking-protocol

What problem does it solve?

This Skill defines a mandatory tracking protocol for coordinating and recording multi-model validation. It ensures pre-launch setup, live progress tracking, failure documentation, consensus analysis, and structured results presentation when running two or more external AI models in parallel.

Core Features & Use Cases

• Pre-launch Checklist: Ensure session, tracking table, and context are prepared before launching models.
• Tracking Table Templates: Standardized tables to capture status, timing, and results.
• Per-Model Status Updates: Immediate updates as each model completes.
• Failure Documentation Protocol: Structured reporting of errors and retries.
• Consensus & Results Presentation: Structured synthesis of model findings.

Quick Start

To begin a multi-model validation, run the pre-launch script to initialize a unique session, session directory, and a tracking.md file. Then launch external models in parallel and, as each completes, update their status in the tracking file.