Use for Clerk backend request auth. PROACTIVELY activate for Express, Fastify, Node, Go, Ruby/Rails, Python/FastAPI/Django/Flask, Java/Spring, C#/.NET, PHP/Laravel, custom APIs, @clerk/express clerkMiddleware()/requireAuth()/getAuth(req), backend request state, cookies, Authorization Bearer tokens, cross-origin frontend-to-API calls, M2M/OAuth/API-key/session token validation, clerkClient Backend API users/orgs calls, proxies/CDNs/CORS/X-Forwarded headers, and 401/404 debugging. Provides middleware patterns, token verification flow, API client guardrails, and language-portable diagnostics.
Use for Clerk JWT and session token clock-skew issues. PROACTIVELY activate for "token-not-active-yet", "JWT cannot be used prior to not before", token-expired, nbf/iat/exp claim failures, clockSkewInMs in verifyToken/authenticateRequest, local dev container/WSL2/Docker Desktop time drift, NTP misconfiguration, paused VM clock, serverless cold-start clock issues, custom JWT template verification leeway across Node/Python/Go/Ruby/Java/.NET/PHP, debugging iat vs server-time delta, and separating real expiry from clock skew. Provides nbf/iat/exp semantics, Clerk and library clock-tolerance defaults, container time fix recipes, multi-language leeway patterns, diagnostics, and gotchas.
Use for Clerk dev/prod readiness, deployment, and multi-language implementation planning. PROACTIVELY activate for environment variables, pk_test/sk_test vs pk_live/sk_live, local dev, preview/staging/prod instances, domains/DNS, redirects, OAuth credentials, custom domains/proxy, authorizedParties, CSP, CORS/cookies, webhooks/tunnels, Vercel/Netlify/Cloudflare/API gateways, monitoring/troubleshooting, and backends in Node/Express/Fastify, Python/FastAPI/Django/Flask, Go, Ruby/Rails, Java/Spring, .NET, PHP/Laravel. Provides checklists, rollout plans, and language-portable patterns.
Use for Clerk frontend auth flows. PROACTIVELY activate for React, JavaScript, Vue, Nuxt, Astro, Expo, React Router, TanStack React Start, or SPA setup; ClerkProvider and publishable-key wiring; SignIn/SignUp/UserButton/UserProfile/OrganizationSwitcher; custom useUser/useAuth/useClerk/useSignIn/useSignUp/useSession/useOrganization flows; multi-session UX; cross-origin getToken() fetches; loading states, redirects, routing, CORS/cookies, or hydration bugs. Provides SDK selection, UI patterns, token-fetch templates, and frontend gotchas.
Use for Clerk in Next.js. PROACTIVELY activate for @clerk/nextjs setup, App Router auth()/currentUser(), clerkMiddleware(), proxy.ts/middleware.ts, createRouteMatcher(), protected pages/layouts/Route Handlers/Server Actions/API routes/tRPC, auth.protect() role/permission/token checks, ClerkProvider placement, server-only clerkClient, Link prefetch, redirects, 401/404 auth failures, custom domains, __clerk proxy paths, and deployment gotchas. Provides file patterns, server/client boundary rules, matcher templates, and production checks.
Use for Clerk sessions, tokens, webhooks, orgs, and security. PROACTIVELY activate for session tokens, JWT templates, getToken(), custom claims, pending sessions, multi-session UX, organizations, roles, permissions, system vs custom permissions, features/plans, MFA/passkeys/password policy/bot protection, Clerk webhooks, Svix signatures, verifyWebhook(), user/org sync, retries/replays, environment variables, custom domains, secret rotation, logs, and auth security reviews. Provides token semantics, webhook idempotency, authorization defaults, and hardening checklist.
This skill should be used when the user asks to automate Azure ML and Azure Data Factory production workflows. PROACTIVELY activate for: (1) Azure ML code asset registration, azure-ai-ml SDK, AML code versions, `result.version`, requested-vs-actual versions, (2) ADF to Azure ML orchestration, ADF WebActivity, managed identity blob reads, `connectVia`, managed VNet IR, (3) code asset version pointer blobs, latest.json contracts, training/scoring code version propagation, (4) private storage firewalls, Microsoft-hosted CI agents, temporary network rules, storage data-plane smoke tests, (5) marshmallow<4 pinning, AML SDK import failures, runtime validation for Azure ML infrastructure. Provides: operationally safe Azure ML + ADF automation patterns.
This skill should be used when the user asks to deploy, scale, or cost-optimize ML workloads on cloud platforms. PROACTIVELY activate for: (1) AWS SageMaker Studio, Training, Processing, Pipelines, Endpoints, Model Monitor, Feature Store, Clarify, Ground Truth, EC2 GPUs, EKS, Lambda, Inferentia, Trainium, (2) GCP Vertex AI Training, Pipelines, Endpoints, Feature Store, Model Monitoring, AutoML, Matching Engine, TPU, GKE, Cloud Run, (3) Azure ML workspaces, pipelines, managed endpoints, AutoML, Responsible ML, AKS/ACI, (4) Databricks, Modal, Replicate, RunPod, Lambda Labs, Anyscale. Provides: cloud ML architecture, autoscaling, hardware, security, and cost guidance.