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Found 2,035 Skills
Master App Store deployment - Submission, TestFlight, CI/CD, release management
Expert ML engineering covering model development, MLOps, feature engineering, model deployment, and production ML systems.
Onnx Converter - Auto-activating skill for ML Deployment. Triggers on: onnx converter, onnx converter Part of the ML Deployment skill category.
Environment variable management across Vercel, Convex, and other platforms. Invoke for: trailing whitespace issues, cross-platform parity, Invalid character errors, webhook secrets, API key management, production deployment, dev vs prod configuration.
Complete guide for Apache Kafka stream processing including producers, consumers, Kafka Streams, connectors, schema registry, and production deployment
Validates entire engineering proof chain. Verifies architecture, backend maps, backend code, standardization, frontend types, infrastructure topology all compose correctly. This is the final DEPLOYMENT GATE - deployment blocked if proof chain invalid. Use when engineering thread completes all actions.
Check and stream Convex deployment logs from the CLI. Use when debugging Convex actions, 401/500 errors, failed queries or mutations, or when you need to see what functions ran and their output.
Create, update, and manage Slot deployments for Katana and Torii services.
Google Cloud Platform CLI (gcloud, gcloud storage, bq). Use when: managing GCP resources, deploying to Cloud Run/Cloud Functions/GKE/App Engine, working with Cloud Storage, BigQuery, IAM, Compute Engine, Cloud SQL, Pub/Sub, Secret Manager, Artifact Registry, Cloud Build, Cloud Scheduler, Cloud Tasks, Vertex AI, VPC/networking, DNS, logging/monitoring, or any GCP service. Also covers: authentication, project/config management, CI/CD integration, serverless deployments, container registry, docker push to GCP, managing secrets, Workload Identity Federation, and infrastructure automation.
This skill provides comprehensive guidance for using the Replicate CLI to run AI models, create predictions, manage deployments, and fine-tune models. Use this skill when the user wants to interact with Replicate's AI model platform via command line, including running image generation models, language models, or any ML model hosted on Replicate. This skill should be used when users ask about running models on Replicate, creating predictions, managing deployments, fine-tuning models, or working with the Replicate API through the CLI.
Fine-tune LLMs with Unsloth using GRPO or SFT. Supports FP8, vision models, mobile deployment, Docker, packing, GGUF export. Use when: train with GRPO, fine-tune, reward functions, SFT training, FP8 training, vision fine-tuning, phone deployment, docker training, packing, export to GGUF.
Ruby on Rails development guidance for building reliable, secure web applications. Covers Rails conventions, MVC architecture, ActiveRecord patterns, background jobs, performance, testing, and deployment.