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Found 1,816 Skills
Archive deployment records with merged common+environment config context (including remote port) for Makefile-first deployment workflow.
Execute deployment through Makefile targets with ENV_MODE and optional VERSION overrides. Use when running real deployment or dry-run preview in Makefile-first workflow.
Netlify JAMstack deployment platform with serverless functions, forms, and identity
Lint Docker Compose files for Makefile-first deployment environments using .deploy.env.common + .deploy.env.<ENV_MODE>. Use when validating local/test/prod/custom compose files for image/build declaration, restart, healthcheck, logging, and external network settings.
Deploy iOS and Android apps to App Store and Google Play. Covers signing, versioning, build configuration, submission process, and release management.
Normalize and validate deployment version under Makefile-first workflow. Use when reading or validating version for test/prod/custom environments before make-based deployment.
Rollback failed deployments, restore previous versions, and handle deployment emergencies. Use when deployments fail, critical bugs are discovered in production, performance degrades after deployment, or emergency recovery is needed.
Implement canary deployment strategies to gradually roll out new versions to subset of users with automatic rollback based on metrics.
Implement blue-green deployment strategies for zero-downtime releases with instant rollback capability and traffic switching between environments.
Use when deploying to Vercel - covers Fluid Compute (timeout issues, 60s bug), vercel.json configuration, maxDuration settings, cron jobs, environment variables (printf gotcha), monorepo setup, Next.js issues, and common build errors
Deploy and serve TensorFlow models
Invoke orq.ai deployments, agents, and models via the Python SDK or HTTP API. Use when a user wants to call a deployment with prompt variables, invoke an agent in a conversation, or call a model directly through the AI Router. Do NOT use for creating or editing deployments/agents (use optimize-prompt or build-agent). Do NOT use for running evaluations (use run-experiment).