What happens if a model version is missing from a checkpoint?

The protocol includes a fallback mechanism that infers the version by analyzing the structural dimensions of the model, such as the observation space and action count, to maintain backward compatibility with legacy models.

Is this skill compatible with CI/CD workflows?

Yes, it includes a strict-version flag that can be enabled in automated testing environments to force a failure if a version mismatch is detected, ensuring only compatible models reach production.

How does the protocol handle different action meanings across versions?

It uses a version-specific action interpretation function that reads the model specification to map integers to specific actions, such as varying position sizes (e.g., 25% vs 50% buy orders).

Why should I embed metadata instead of using versioned filenames?

Embedding metadata directly in the checkpoint ensures the configuration is physically tied to the model weights, preventing accidental mismatches that occur when files are renamed or moved.

Model Version Protocol

Name: Model Version Protocol
Author: smith6jt-cop

bysmith6jt-cop

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Data Science & ML

Manages version compatibility between trained trading models and live trading environments by embedding metadata into checkpoints.

The Model Version Protocol is a specialized framework designed to prevent silent failures in algorithmic trading by ensuring strict compatibility between training code and live trading bots. By embedding explicit version metadata—including observation dimensions, action spaces, and specific feature mappings—directly into model checkpoints, it enables automated validation at load time. This skill is particularly useful for quant developers and ML engineers who frequently update training architectures and need a reliable way to manage breaking changes, ensuring that the live trader interprets model outputs correctly regardless of which version is deployed.

Key Features

01Legacy model detection using structural inference (obs_dim/n_actions)

02Compatibility matrix mapping model versions to trader requirements

03Strict and soft validation modes for CI/CD and manual testing

040 GitHub stars

05Dynamic action interpretation based on version-specific schemas

06Automated version metadata embedding in model checkpoints

Use Cases

01Managing multiple generations of PPO models during rapid experimentation

02Preventing live trading bots from loading models with incompatible action spaces

03Automating deployment checks to verify model-trader alignment in production

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add smith6jt-cop/skills_registry model-version-protocol

For use in Claude.ai and ChatGPT

Download Skill