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choijinwon
choijinwonCOMMUNITY
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agent-mlflow-skill-mlflow-verify

Verify MLflow runs and model registry entries in OpenCode ML workspaces.

1|Updated Jun 18, 2026
Search Tags:#MLflow#OpenCode#run status#model verification#MLregistry
One-click install
npx skills add https://github.com/choijinwon/opecode-ml-skill- --skill agent-mlflow-skill-mlflow-verify
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-mlflow-skill-mlflow-verify
Source: https://github.com/choijinwon/opecode-ml-skill-/tree/main/.opencode/skills/agent-mlflow-skill-mlflow-verify
Command: npx skills add https://github.com/choijinwon/opecode-ml-skill- --skill agent-mlflow-skill-mlflow-verify

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mlflow, and includes scripts (resource) components.

What problem does it solve?

This Skill solves the problem of confirming MLflow runs, artifacts, and models for OpenCode ML workspaces, providing a detailed verification for model integrity and setup.

Core Features & Use Cases

  • MLflow Run Verification: Ensures that runs, params, metrics, and artifacts are properly recorded in MLflow.
  • Model Registry Check: Confirms the creation of model versions in Model Registry.
  • Environment Verification: Differentiates between local and remote MLflow tracking locations.

Quick Start

Execute the agent-mlflow-skill-mlflow-verify command in your OpenCode workspace to check MLflow runs and model registry status.

Frequently Asked Questions about agent-mlflow-skill-mlflow-verify

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

FAQPage Schema
How do I verify MLflow run status and logged artifacts in OpenCode workspaces?▼

You can verify MLflow run status by executing the verification command in your OpenCode workspace, which checks that runs, params, metrics, and artifacts are properly recorded in MLflow tracking.

How do I check if my models are properly registered in the MLflow Model Registry?▼

To check the MLflow Model Registry, run the verification command to confirm the creation of model versions and ensure all registry entries are properly logged within your workspace.

Can I verify MLflow tracking for both local and remote environments?▼

Yes, you can verify MLflow tracking for both local and remote environments, as the verification process differentiates tracking locations to confirm proper setup and model integrity.

What does MLflow verification check for model integrity and setup?▼

MLflow verification checks for model integrity by confirming proper tracking of runs, validating model registry entries, and ensuring artifacts and logging details are correctly recorded in the workspace.

Do I need the mlflow package installed to verify runs and models in OpenCode?▼

Yes, the mlflow package must be installed as a dependency to verify runs and models, because the verification process directly queries MLflow tracking entries, artifacts, and model registry status.

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