AI Model Registry
Centralized management of machine learning models throughout their lifecycle, including versioning, metadata, and production deployment.
npx skills add majiayu000/claude-skill-registry --skill model-registry-amnadtaowsoam-cerebratechai-claude --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# AI Model Registry ## Overview An AI Model Registry is a central repository used by data scientists and ML engineers to store, manage, and version machine learning models. It acts as the "source of truth" for models, tracking everything from hyperparameters to production status. **Core Principle**: "Models are software artifacts. They must be versioned, audited, and controlled with the same rigor as source code." --- ## 1. Why a Model Registry is Essential Without a registry, models are often stored as files like `model_v2_final_final.pkl` in S3 buckets, leading to: * **Shadow Models**: Models running in production that no one can find the source for. * **Version Mismatch**: Predicting with `v2` code but `v1` model weights. * **Lack of Audit**: Inability to explain why a model was promoted to production. --- ## 2. Core Components of a Registry | Component | Description | | :--- | :--- | | **Versioning** | Tracking major and minor changes (e.g., `v1.0.0` -> `v1.1.0`). | | **Metadata** | Storing hyperparameters, training datasets, and performance metrics. | | **Artifacts** | The actual binary files (Pickles, ONNX, TensorFlow SavedModel). | | **Lineage** | Linking the model to the ex
- Overview
- 1. Why a Model Registry is Essential
- 2. Core Components of a Registry
- 3. Implementation with MLflow
- Registering a Model (Python)
- Transitioning Stages
- 4. Model Metadata: The "Model Card"
- 5. Model Deployment Patterns
- 6. Registry Tools Landscape
- 7. Model Audit and Compliance
- 8. Real-World Scenario: The "Zombie" Pricing Model
- 9. AI Model Registry Checklist
- Related Skills
What does the AI Model Registry skill do?
Centralized management of machine learning models throughout their lifecycle, including versioning, metadata, and production deployment.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill model-registry-amnadtaowsoam-cerebratechai-claude --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.