Help users set up mirrord in CI pipelines for testing against real Kubernetes environments. Use when users want to run end-to-end tests, integration tests, or automated tests in…
Helps users generate, edit, and validate mirrord.json configuration files for mirrord (MetalBear). Use when the user wants to connect their local process to a Kubernetes…
Help users install and configure the mirrord operator for team environments. Use when users ask about operator setup, Helm installation, licensing, or multi-user mirrord…
Help users create and manage mirrord preview environments — running a modified service as an isolated pod in a shared Kubernetes cluster, scoped by an environment key and…
Guide users from zero to their first working mirrord session. Use when a user is new to mirrord, wants to install it, or needs help running their first session connecting to a…
Use when the user wants to install, pin, or switch language/runtime versions per repository - node, python, go, ruby, java, rust, deno, bun, terraform, etc.
Generate an operational runbook through Mission Control. Use when the user wants RUNBOOK.md or a chat-native runbook covering startup, tests, build, debugging, local reset, logs,…
Switch Mission Control toward local-first behavior. Use when the user wants local files, local models, no cloud deployment, and no external APIs unless explicitly approved.
Route TensorFlow Lite export and edge-readiness checks through Mission Control with explicit artifact and constraint validation.
Deploy Mistral AI integrations to Vercel, Docker, and Cloud Run platforms. Use when deploying Mistral AI-powered applications to production, configuring platform-specific secrets,…
Configure Mistral AI across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or…
Execute Mistral AI production deployment checklist and rollback procedures. Use when deploying Mistral AI integrations to production, preparing for launch, or implementing go-live…
Ship FP16, BF16, or FP8 training and inference that holds accuracy while capturing the speedup, using loss scaling and numeric validation.
Prepares ML models for production deployment with containerization, API creation, monitoring setup, and A/B testing.
Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation.
Use when the user wants to verify code, config, or math before running — or proactively before any expensive training job or deployment
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback.
MLOps and the production ML lifecycle -- model packaging and serving, CI/CD for ML, experiment tracking, model registries, reproducibility, production monitoring for data and…
Cloud database platform specialist covering Neon (serverless PostgreSQL), Supabase (PostgreSQL 16 with real-time), and Firebase Firestore (NoSQL with offline sync).
Deployment and hosting platform specialist covering Vercel, Railway, and Convex. Use when deploying applications, configuring edge functions, setting up continuous deployment, or…
Set up mobile CI/CD pipelines for Flutter, React Native, or native iOS/Android — GitHub Actions workflows for testing, code signing, TestFlight/Play Store distribution, build…
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or…
Upgrade shared Modal runtime dependencies in kernelbot and verify them end to end. Use when changing torch/CUDA or other shared Modal image dependencies, deploying the Modal app,…
Deploy AI workloads to serverless GPU/CPU with Modal — define @app.function with GPU/memory specs, build custom container images, run batch jobs and web endpoints, schedule cron…
Document a deployed ML/AI model so others can use it responsibly. Use when asked to write a model card, document a model's intended use and limitations, or prepare an AI model for…
Generates a Jupyter notebook that deploys fine-tuned models from SageMaker Serverless Model Customization to SageMaker endpoints or Bedrock.
Use when you have a pre-trained Keras model and need to deploy it via a Docker-based TensorFlow Serving API (e.g., for molecular classification via SMILES), but the model's layer…
Model Drift Detector - Auto-activating skill for ML Deployment. Triggers on: model drift detector, model drift detector Part of the ML Deployment skill category.
Model Export Helper - Auto-activating skill for ML Deployment. Triggers on: model export helper, model export helper Part of the ML Deployment skill category.
Use when after starting a TensorFlow Serving instance (e.g., via docker-compose)
Use when after deploying a TensorFlow Serving container (especially within a Dockerized stack like NP-Classifier), before running classification or inference pipelines, to confirm…
Model Pruning Helper - Auto-activating skill for ML Deployment. Triggers on: model pruning helper, model pruning helper Part of the ML Deployment skill category.
Model Quantization Tool - Auto-activating skill for ML Deployment. Triggers on: model quantization tool, model quantization tool Part of the ML Deployment skill category.
Model Versioning Manager - Auto-activating skill for ML Deployment. Triggers on: model versioning manager, model versioning manager Part of the ML Deployment skill category.
Builds fund economic models with sensitivity across deployment pace, exit multiples, and fee/carry structures for LP and GP returns.
Curated bundle for managing monorepos with containerized deployment pipelines. Includes monorepo management, Docker containerization, CI/CD deployment, and coding standards.
Guides creation of Monte Carlo monitors via MCP tools, producing monitors-as-code YAML for CI/CD deployment.
Automatically diagnose Mooncake deployment and runtime issues. Checks services (mooncake_master, metadata server), RDMA devices, environment variables, connectivity, memory…
Run MOOSE finite-element simulations on Windows via Docker. Use when creating, running, debugging, or visualizing MOOSE input files (.i).
Deliver repeatable MotherDuck architectures across multiple clients. Use when a consultancy, agency, or multi-client product team needs to standardize isolation, provisioning,…
Motoko language pitfalls, modern syntax, and architecture patterns for the Internet Computer. Covers persistent actors, stable types, mo:core standard library, dot notation,…
You are an advanced Docker containerization expert with comprehensive, practical knowledge of — from MrJmpl3/opencode_____data_____configuration
Use when when you have MS/MS spectral data (raw or intermediate format) that must be fed into the Mass2SMILES Docker container or similar deep learning models for…
Implement, review, or test Market Signal Pipeline Google Cloud and Terraform deployment work. Use for Cloud Scheduler, Pub/Sub, authenticated push subscriptions, Cloud Run,…
Designing, orchestrating, and maintaining multi-package architectures in Salesforce DX: dependency DAG design, layered package decomposition, install ordering, cross-package API…
Use when you need to validate that Docker image builds for multiple deployment variants (e.g., cli, dev, linux, windows) meet documented compressed size ranges, or when you must…
Review multi-tenant AI deployments for cross-tenant context leakage, LoRA adapter contamination, shared inference worker risks, system prompt bleed, and tenant isolation failures…
Use when when deploying a Streamlit workflow app in offline mode (online_deployment:
Guide users through the MUXI platform -- infrastructure for AI agents. Covers installation (CLI and server), server setup and configuration, CLI commands and workflows, secrets…
Use when users ask about MyBrain, what it does, how it works, what tools are available, or how to use the personal knowledge base.
Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS.
Execute Vast.ai production deployment checklist and rollback procedures. Use when deploying Vast.ai integrations to production, preparing for launch, or implementing go-live…
Execute CodeRabbit production deployment checklist and rollback procedures. Use when deploying CodeRabbit integrations to production, preparing for launch, or implementing go-live…
Provides AWS CloudFormation patterns for Amazon RDS databases. Use when creating RDS instances (MySQL, PostgreSQL, Aurora), DB clusters, multi-AZ deployments, parameter groups,…
Terraform Module Creator - Auto-activating skill for DevOps Advanced. Triggers on: terraform module creator, terraform module creator Part of the DevOps Advanced skill ca — from…
Agent Script DSL development skill for Salesforce Agentforce. Enables writing deterministic agents in a single .agent file with FSM architecture, instruction resolution — from…
Agent Script DSL development skill for Salesforce Agentforce. Enables writing deterministic agents in a single .agent file with FSM architecture, instruction resolution — from…
Manage kubernetes secrets manager operations. Auto-activating skill for DevOps Advanced. Triggers on: kubernetes secrets manager, kubernetes secrets manager Part of the DevOps…
NASA Systems Engineering methodology mapped to cloud operations. Use when planning, executing, verifying, or documenting OpenStack cloud infrastructure following NASA SP-6105 and…
Use when deploying Navan integrations with ERP systems (NetSuite, Sage Intacct, Xero), HRIS platforms (Workday, BambooHR), or identity providers (Okta, Azure AD).