Results for “versioning”

Manages the machine learning lifecycle with experiment tracking, model versioning, reproducible runs, and deployment through the MLflow platform.

Designs and implements enterprise GitOps workflows: branching strategies, release automation, semantic versioning, conventional commits, and git hooks.

A git SHA pins the transformation.

Design REST and GraphQL APIs with OpenAPI 3.1 specifications, resource modeling, versioning strategies, pagination patterns, and error handling standards.

Design consistent REST APIs with resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting.

Builds reusable CircleCI Orbs with the Orb SDK and orb-tools pipeline, packaging commands, executors, and jobs with automated semantic versioning.

Manages the lifecycle of large language models in production, covering model versioning, prompt management, inference optimization, and cost control.

REST API design — resource naming, HTTP methods, status codes, pagination, versioning, OpenAPI. Use when designing a new REST API, reviewing API contracts, writing OpenAPI/Swagger documentation, or choosing pagination, versioning, or error-format strategies.

MLflow, model versioning, experiment tracking, model registry, and production ML systems

Expert at designing clean, consistent, and developer-friendly APIs. Covers RESTful conventions, versioning strategies, error handling, pagination, rate limiting, and OpenAPI documentation. Designs APIs that are intuitive to use and easy to evolve. Use when "API design, REST API, RESTful, API versioning, API documentation, OpenAPI, Swagger, API error handling, pagination, rate limiting, api, rest, http, versioning, pagination, openapi, swagger" mentioned.

Defines RESTful API design conventions including URL structure, status codes, error formats, pagination, versioning, rate limiting, CORS, validation, and OpenAPI documentation.

Migrate .NET projects from per-project package versioning to NuGet Central Package Management (CPM) using Directory.Packages.props, with baseline build capture, version conflict resolution, and post-conversion validation.

Semantic versioning releases — version bumps, changelogs, tags, publishing. Use when preparing a new release: deciding the version bump, drafting the changelog, tagging the commit, and publishing to the project's distribution channel.

Define version control strategies for design files, component libraries, and design assets to enable team collaboration and consistency.

Manages AI model retention and machine unlearning requirements. Covers training data deletion verification, model versioning for compliance, machine unlearning techniques (SISA, gradient-based), and retraining triggers. Keywords: AI retention, machine unlearning, model versioning, training data deletion, retraining, storage limitation.

Version bump, generate changelog, tag, and prepare a release

Automates semantic versioning and release workflow for Claude Code plugins, including version increments across multiple manifest files, build verification, git tagging, GitHub releases, and changelog generation.

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Run any Replicate model (image gen, audio, video) by version ID

Use when the user asks to release, version, tag, or publish.

Read, create, and review PDF files with visual rendering checks using Poppler, reportlab, pdfplumber, and pypdf.

Manage Git repositories and collaborative workflows — branching strategies, commit hygiene, conflict resolution, pull requests, hooks, and .gitignore management. Use when the user requests version control or provides relevant inputs for this workflow.

Deploy a trained model to serving with versioning, shadow or canary rollout, and a tested rollback path.

Enforces the Vikingo Studio standard for WordPress plugins and repos: naming taxonomy, plugin headers, folder structure, versioning, release flow, private update channel, admin UI rules, security baseline, and pre-release checklist.

Data Version Control for ML projects. Track large datasets and models alongside Git, build reproducible ML pipelines, and run experiments with metric comparison. Works with any storage backend including S3, GCS, Azure, and local filesystems.

Structures git workflow practices for committing, branching, resolving conflicts, and organizing work across multiple parallel streams.

Begins a new version release using git-flow. This skill should be used when the user asks to "start a release", "create release branch", "prepare a release", "git flow release start", or wants to begin a new version release. Accepts either an explicit version or a natural-language description of the release.

MVCC (Multi-Version Concurrency Control)

Reproduces an existing design as a faithful, self-contained HTML file, then generates and evaluates design variations to recommend the strongest option.

Migrates code between frameworks, versions, or patterns safely