Automate application deployment to cloud platforms and servers. Use when setting up CI/CD pipelines, deploying to Docker/Kubernetes, or configuring cloud infrastructure. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.

Automate Box cloud storage operations including file upload/download, search, folder management, sharing, collaborations, and metadata queries via Rube MCP (Composio). Always search tools first for current schemas.

Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration. Use PROACTIVELY for testing automation or quality assurance.

Automate Vercel tasks via Rube MCP (Composio): manage deployments, domains, DNS, env vars, projects, and teams. Always search tools first for current schemas.

Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies.

Automated cleanup of unused AWS resources to reduce costs

Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing c...

Manage AI Kitchen Pro Stripe webhook — deploy, test, switch test/prod, view logs

Manage expense tracker bot — deploy, check expenses, export data, sync locally

Website deployment via GitHub PR + Cloud Build

LOCAL-ONLY PyPI publishing with Doppler credentials. TRIGGERS - publish to PyPI, pypi upload, local publish. NEVER use in CI/CD.

ClickHouse Cloud user and permission management. TRIGGERS - create ClickHouse user, ClickHouse permissions, ClickHouse Cloud credentials.

Cal.com self-hosted deployment to GCP Cloud Run with Supabase PostgreSQL. Docker Compose for local dev.

STUB — bundle, sanitize, upload Claude Code sessions to Cloudflare R2, emit 7-day presigned URL.

CCaaS platform comparison and selection — choosing the right cloud contact center (Genesys Cloud CX, NICE CXone, Talkdesk, Five9, 8x8, Nextiva, Amazon Connect, Twilio Flex, Aircall, Dialpad). Use when comparing CCaaS platforms for a contact center, deciding between Genesys vs NICE CXone vs Talkdesk vs Five9, evaluating pricing tiers across contact center platforms, choosing a CCaaS for a specific team size or industry, migrating from on-prem (Avaya, Cisco, Mitel) to cloud contact center, or wondering which CCaaS has the best WFM or AI features. Do NOT use for platform-specific configuration help (use /sales-genesys, /sales-nice-cxone, or /sales-talkdesk) or for QA/coaching tool selection (use /sales-coaching).

Lemon Squeezy platform help — payments, subscriptions, tax compliance, digital product delivery, license keys, and checkout as a merchant of record. Use when setting up a Lemon Squeezy store, configuring subscriptions or usage-based billing, generating or validating license keys, webhooks aren't firing or Cloudflare is blocking them, payouts are delayed or frozen, or choosing between Lemon Squeezy vs Gumroad vs Paddle. Do NOT use for general email marketing strategy (use /sales-email-marketing) or checkout optimization strategy (use /sales-checkout).

MaxIQ platform help — AI-native revenue intelligence with EchoIQ conversation intelligence, InspectIQ pipeline visibility, ForecastIQ AI-driven forecasting, 9 AI agents (NoteTaker, Radar, Summarizer, Coach, Taskmaster, Watchdog, Forecaster, Revenue Planner, Deal Mapper), usage-based pricing (no per-seat), Salesforce/HubSpot CRM sync. Use when EchoIQ not capturing all meeting types, AI Coach scoring criteria not matching your sales process, CRM fields not auto-populating from calls, InspectIQ deal signals seem inaccurate, ForecastIQ predictions not matching reality, comparing MaxIQ vs Gong vs Clari for revenue intelligence, setting up AI Radar keyword tracking, or evaluating usage-based CI pricing vs per-seat alternatives. Do NOT use for designing outbound cadences (use /sales-cadence) or cross-platform coaching programs (use /sales-coaching).

Proshort platform help — enablement-first conversation intelligence with contextual AI coaching, AI Roleplay, CRM auto-sync, deal risk alerts. Use when setting up Proshort call recording on Zoom/Meet/Teams, configuring AI Roleplay for rep onboarding, Proshort deal risk alerts not appearing in Slack, Proshort CRM auto-sync not populating Salesforce/HubSpot/Zoho fields, comparing Proshort vs Gong vs Avoma vs Rafiki for mid-market CI, choosing an enablement-first CI platform that combines coaching with call analysis, or evaluating Proshort pricing ($75/user/mo) against alternatives. Do NOT use for reviewing a single call for coaching (use /sales-call-review) or building a coaching program across tools (use /sales-coaching).

Uniphore platform help — Business AI Cloud for enterprise contact centers with conversation intelligence, real-time agent assist (U-Assist), automated QA, CSATai predictive scoring, Emotion AI, self-service virtual agents, and CDP (ActionIQ). Use when setting up Uniphore conversation analytics, configuring U-Assist real-time guidance, building automated QA scorecards on 100% of calls, using CSATai to replace CSAT surveys, deploying Emotion AI for sentiment detection, integrating Uniphore with Genesys or Salesforce or Five9, comparing Uniphore vs NICE vs Verint vs Observe.AI, or troubleshooting ActionIQ CDP segments. Do NOT use for CCaaS platform comparison (use /sales-ccaas-selection) or general coaching strategy (use /sales-coaching).

Solidroad platform help — AI-powered QA and training for CX teams. Use when reps ramping too slowly and need AI practice simulations, QA only covers 2% of conversations and you want 100% automated scoring, training and QA are disconnected and insights don't turn into coaching, setting up Solidroad scorecards or custom quality rubrics, connecting Solidroad to Salesforce Service Cloud or Zendesk or Intercom, or evaluating Solidroad vs Observe.AI vs Balto vs Cresta for contact center QA. Do NOT use for general coaching strategy without a specific platform (use /sales-coaching).

Complete Git expertise system for ALL git operations. PROACTIVELY activate for: (1) ANY Git task (basic/advanced/dangerous), (2) Repository management, (3) Branch strategies and workflows, (4) Conflict resolution, (5) History rewriting/recovery, (6) Platform-specific operations (GitHub/Azure DevOps/Bitbucket), (7) Advanced commands (rebase/cherry-pick/filter-repo). Provides: complete Git command reference, safety guardrails for destructive operations, platform best practices, workflow strategies, reflog recovery techniques, and expert guidance for even the most risky operations. Always asks user preference for automatic commits vs manual control.

Azure Machine Learning Workspace and Azure AI Foundry deep dive. PROACTIVELY activate for: (1) creating and configuring Azure ML workspaces, (2) Azure AI Foundry hubs and projects, (3) ML workspace networking (managed VNet, private endpoints, DNS), (4) ML compute clusters and compute instances, (5) managed online endpoints, batch endpoints, Kubernetes endpoints, (6) managed identities for ML resources, (7) ACR integration for custom environments, (8) storage account configuration, (9) az ml CLI v2 commands, (10) PowerShell Az.MachineLearningServices, (11) reading ML compute and deployment logs, (12) GPU SKU selection (ND/NC series, H100/H200/A100). Provides: workspace setup playbook, network-isolation patterns, endpoint deployment templates, az ml CLI cheat sheet, and log diagnosis workflow.

Azure Data Factory (ADF) CI/CD, deployment, and pipeline development. PROACTIVELY activate for: (1) ADF CI/CD setup (npm validation, ARM template export), (2) ADF ARM template deployment, (3) ADF npm build validation in CI, (4) PrePostDeploymentScript for trigger and resource cleanup, (5) ADF GitHub Actions workflows, (6) ADF Azure DevOps pipelines, (7) ADF Git integration (collaboration vs publish branch), (8) parameterizing linked services and datasets across environments, (9) ADF triggers (schedule, tumbling window, event), (10) deployment slots and blue-green for ADF. Provides: complete CI/CD YAML for GitHub Actions and Azure DevOps, PrePostDeploymentScript reference, parameterization patterns, and trigger management recipes.

Expert bash/shell scripting across environments where Bash is available (Linux, macOS, Git Bash on Windows, WSL, containers). This is a Bash-focused skill - it does not provide PowerShell parity; on Windows the target is the Bash interpreter (Git Bash / WSL), not native PowerShell. PROACTIVELY activate for: (1) ANY bash/shell script task, (2) System automation, (3) DevOps/CI/CD scripts, (4) Build/deployment automation, (5) Script review/debugging, (6) Converting commands to scripts. Provides: Google Shell Style Guide compliance, ShellCheck validation, Bash portability across Linux/macOS/WSL/Git Bash/containers, POSIX compliance, security hardening, error handling, performance optimization, testing with BATS, and production-ready patterns. Ensures professional-grade, secure, portable Bash scripts every time.

Complete PowerShell expertise system across ALL platforms (Windows/Linux/macOS). PROACTIVELY activate for: (1) ANY PowerShell task (scripts/modules/cmdlets), (2) CI/CD automation (GitHub Actions/Azure DevOps/Bitbucket), (3) Cross-platform scripting, (4) Module discovery and management (PSGallery), (5) Azure/AWS/Microsoft 365 automation, (6) Script debugging and optimization, (7) Best practices and security. Provides: PowerShell 7+ features, popular module expertise (Az, Microsoft.Graph, PnP, AWS Tools), PSGallery integration, platform-specific guidance, CI/CD pipeline patterns, cmdlet syntax mastery, and production-ready scripting patterns. Ensures professional-grade, cross-platform PowerShell automation following industry standards.

TMDL and PBIR validation, linting, and pre-deployment testing. PROACTIVELY activate for: (1) validating TMDL syntax before deploy, (2) validating PBIR schema, (3) catching TmdlFormatException / TmdlSerializationException early, (4) Best Practice Analyzer (BPA) rules and BPA CLI, (5) Tabular Editor BPA scripting, (6) PBI-Inspector / PBI-InspectorV2 / Fab Inspector, (7) PBIR JSON schema validation, (8) pre-deployment validation in CI, (9) fabric-cicd parameter.yml validation, (10) catching breaking changes between TMDL versions. Provides: BPA rule library, validation CLI commands, CI integration for validation, error catalog (TmdlFormatException, etc.), and a pre-deploy validation playbook.

TMDL (Tabular Model Definition Language) mastery for Power BI semantic models. PROACTIVELY activate for: (1) writing or editing TMDL files, (2) TMDL syntax (model.tmdl, database.tmdl, relationships.tmdl, table folders), (3) TMDL serialization (TmdlSerializer, folder-based vs single-file), (4) TMDL view in Power BI Desktop, (5) TMDL vs TMSL vs BIM format selection, (6) TMDL expressions, calculation groups, perspectives, cultures, translations, annotations, (7) TMDL roles and security, (8) TMDL ref keyword and createOrReplace scripts, (9) TMDL CI/CD integration (Git, deployment), (10) TMDL hierarchies and partitions. Provides: TMDL syntax reference, folder-layout templates, serialization patterns, ref/createOrReplace recipes, and Git integration setup.

OpenTofu (Terraform open-source fork) guide and migration. PROACTIVELY activate for: (1) OpenTofu installation and tofu CLI usage, (2) migrating from Terraform CLI to OpenTofu, (3) provider compatibility between Terraform and OpenTofu, (4) state file compatibility, (5) OpenTofu-specific features (encrypted state, dynamic provider config), (6) Terraform Registry vs OpenTofu Registry, (7) CI/CD with OpenTofu (GitHub Actions, Azure DevOps), (8) HashiCorp BSL license vs OpenTofu MPL, (9) using OpenTofu with Terragrunt. Provides: migration checklist, CLI command mapping, encrypted state setup, registry comparison, and CI YAML templates.

Power BI deployment, CI/CD, governance, and administration. PROACTIVELY activate for: (1) Power BI deployment pipelines (Service deployment pipelines, fabric-cicd, custom workflows), (2) CI/CD for Power BI via GitHub Actions or Azure DevOps, (3) workspace management and roles, (4) row-level security (RLS) and object-level security (OLS), (5) capacity management (Premium, PPU, Fabric SKUs F2-F2048), (6) tenant settings and governance, (7) Power BI Report Server deployments, (8) service principal setup for automation, (9) data-gateway management. Provides: deployment-pipeline templates, GitHub Actions and Azure DevOps YAML, RLS/OLS implementation patterns, capacity sizing guidance, and service-principal auth recipes.

Azure Deployment Stacks for unified resource lifecycle management. PROACTIVELY activate for: (1) Azure Deployment Stacks (GA replacement for Azure Blueprints), (2) deny settings (DenyDelete, DenyWriteAndDelete) for resource protection, (3) ActionOnUnmanage behavior (delete, detach), (4) Bicep deployment stacks, (5) cross-subscription stack deployments, (6) updating an existing stack (resource adoption), (7) inspecting stack resources and history, (8) stack vs traditional deployment tradeoffs, (9) GitOps with deployment stacks. Provides: Bicep stack templates, az stack CLI reference, deny-settings matrix, and migration guidance from Blueprints.

Salesforce Hyperforce public cloud infrastructure and architecture (2025). PROACTIVELY activate for: (1) understanding Hyperforce architecture (multi-region, public cloud), (2) Hyperforce migration planning, (3) data residency and regional deployments, (4) Hyperforce security model (BYOK, Shield encryption), (5) network architecture (PrivateLink, public IP allowlists), (6) Hyperforce vs first-generation infrastructure differences, (7) backup and disaster recovery on Hyperforce, (8) Hyperforce performance and SLA, (9) compliance certifications (HIPAA, FedRAMP, GDPR). Provides: Hyperforce overview, migration checklist, network architecture patterns, BYOK setup, and DR/backup configuration.

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.

Docker Compose production patterns for 2025 (multi-environment, health checks, modern features). PROACTIVELY activate for: (1) production Docker Compose patterns, (2) multi-environment strategies (compose.override.yml, compose.production.yml), (3) HEALTHCHECK and depends_on with conditions (service_healthy, service_started), (4) Compose v2 features (profiles, includes, watch), (5) secrets and configs (Compose secrets), (6) network segmentation in Compose, (7) resource limits (deploy.resources), (8) restart policies, (9) Compose for swarm vs standalone, (10) migrating from v3 to current Compose Spec. Provides: production compose templates, multi-env override patterns, healthcheck recipes, secrets handling, and Compose Spec migration.

Azure Kubernetes Service (AKS) Automatic mode and 2025 platform features. PROACTIVELY activate for: (1) AKS Automatic (managed Kubernetes, zero operational overhead), (2) Karpenter-based autoscaling on AKS, (3) NodePool CRD usage, (4) HPA, VPA, KEDA on AKS, (5) workload identity and Microsoft Entra integration, (6) AKS billing model (Automatic vs Standard), (7) AKS 2025 cluster defaults (RBAC, Azure CNI overlay, Cilium), (8) AKS upgrade and version management, (9) GitOps on AKS (Flux, ArgoCD), (10) AKS observability (Azure Monitor for containers, Managed Prometheus). Provides: AKS Automatic vs Standard comparison, Karpenter setup, workload-identity recipes, KEDA scaler patterns, and an end-to-end AKS Automatic deployment guide.

Azure Container Apps with GPU support, serverless capabilities, and Foundry Models. PROACTIVELY activate for: (1) Container Apps GPU (serverless GPU workloads), (2) Container Apps with Dapr integration, (3) scale-to-zero AI workloads, (4) Container Apps Jobs (one-shot, scheduled, event-driven), (5) Container Apps Foundry Models integration, (6) revisions and traffic splitting, (7) custom domains and managed certificates, (8) ingress and authentication, (9) Container Apps Environment configuration, (10) Workload Profiles (Consumption vs Dedicated). Provides: GPU SKU reference, scale rule examples (HTTP, KEDA), Dapr building-block recipes, traffic-split patterns, and end-to-end serverless GPU deployment.

Modern DevOps and CI/CD bash automation patterns with containers and cloud (2025). PROACTIVELY activate for: (1) writing CI/CD scripts (GitHub Actions, GitLab CI, Azure DevOps), (2) container-aware shell scripting (detecting containers, Kubernetes pods), (3) cloud provider helpers (AWS CLI, Azure CLI, gcloud), (4) blue-green and canary deployments via bash, (5) writing idempotent rollback scripts, (6) integrating with Docker/Compose from bash, (7) cross-environment variable management, (8) build matrix orchestration. Provides: copy-pasteable CI snippets, container detection helpers, cloud CLI wrappers, deployment orchestration patterns, and idempotent rollback templates.

Azure DevOps Sprint 254-262 new features and enhancements (2025). PROACTIVELY activate for: (1) checking what is new in recent Azure DevOps sprints, (2) using new pipeline tasks introduced in Sprint 254+, (3) Azure Boards updates (delivery plans, query enhancements), (4) Azure Repos updates (branch policies, advanced security), (5) Azure Pipelines updates (1ES hosted pools, agent retirement), (6) Azure Artifacts updates (upstream sources, retention), (7) deprecation notices (TFVC, classic pipelines), (8) GitHub Advanced Security for ADO. Provides: sprint-by-sprint changelog, new feature reference, deprecation timeline, and migration notes.

Windows and Git Bash testing compatibility for Vitest, Playwright, and MSW. PROACTIVELY activate for: (1) Vitest tests failing on Windows but passing on Linux, (2) Playwright on Windows with Git Bash quirks, (3) MSW intercept issues across shells, (4) path normalization in test fixtures, (5) browser binaries on Windows (Playwright install), (6) line-ending issues in test snapshots (CRLF vs LF), (7) cross-platform test scripts in package.json, (8) shell detection in pretest/posttest hooks, (9) CI-on-Windows debugging. Provides: cross-platform package.json scripts, snapshot normalization, Playwright Windows install, MSW shell-aware setup, and CI Windows debugging recipes.

Comprehensive bash script debugging and troubleshooting techniques for 2025. PROACTIVELY activate for: (1) debugging a misbehaving bash script, (2) using set -x, set -e, set -u, set -o pipefail (strict mode), (3) customizing PS4 for richer trace output, (4) trap DEBUG, ERR, and EXIT for diagnostics, (5) bashdb and other interactive debuggers, (6) profiling slow scripts (timing, BASH_REMATCH overhead), (7) reproducing CI-only failures locally, (8) resolving unbound variable or command not found errors, (9) understanding subshell vs current-shell variable scope. Provides: strict-mode template, PS4 patterns, trap recipes for instrumentation, profiling techniques, and a step-by-step debugging playbook.

This skill should be used when the user asks to productionize, track, version, govern, monitor, or automate ML systems. PROACTIVELY activate for: (1) MLflow, Weights & Biases, Neptune, Comet, ClearML experiment tracking, (2) model registry, model versioning, artifact lineage, reproducibility, (3) Kubeflow, SageMaker Pipelines, Vertex AI Pipelines, Azure ML pipelines, Databricks workflows, (4) CI/CD, continuous training/evaluation, A/B tests, canary/shadow deployments, (5) drift detection, model monitoring, data validation, responsible AI governance. Provides: end-to-end MLOps architecture and operational safeguards.

Unity Editor tooling, build automation, and asset pipeline customization. PROACTIVELY activate for: (1) writing custom Editor scripts, (2) custom inspectors and PropertyDrawer attributes, (3) EditorWindow creation, (4) ScriptedImporter for custom asset types, (5) build pipeline scripting (BuildPipeline.BuildPlayer, IBuildPostprocessor), (6) platform-switching automation, (7) CI/CD for Unity (GameCI, GitHub Actions, Unity Build Automation), (8) Assembly Definition (.asmdef) organization, (9) preprocessor symbols and platform defines, (10) Editor-only code with #if UNITY_EDITOR. Provides: custom inspector templates, EditorWindow examples, build script patterns, GameCI setup, .asmdef best practices, and CI YAML for Unity builds.

GitHub Actions 2025-2026 features and modernization. PROACTIVELY activate for: (1) 1 vCPU Linux runners (October 2025 public preview), (2) immutable releases for hardened distribution, (3) Node24 migration from Node20, (4) reusable workflows and composite actions, (5) workflow_dispatch with rich inputs, (6) artifact attestations and provenance, (7) ARC (Actions Runner Controller) for self-hosted Kubernetes, (8) larger runners and macOS Apple Silicon runners, (9) deployment environments and protection rules, (10) OIDC federation to AWS/Azure/GCP. Provides: workflow templates, runner-selection matrix, OIDC setup recipes, attestation patterns, and Node24 migration steps.

Complete Python GitHub Actions system. PROACTIVELY activate for: (1) uv-based CI workflows (10-100x faster), (2) Matrix testing across Python versions, (3) Dependency caching with setup-uv, (4) Parallel test execution, (5) Reusable workflows, (6) Publishing to PyPI with trusted publishing, (7) Code coverage with codecov, (8) Security scanning. Provides: Workflow templates, caching config, matrix strategies, composite actions. Ensures fast, reliable CI/CD pipelines.

ShellCheck validation as a non-negotiable 2025 workflow practice. PROACTIVELY activate for: (1) running ShellCheck on bash scripts, (2) interpreting and fixing ShellCheck warnings (SC2086, SC2068, SC2155, SC2295, SC2327, SC2328, SC2294), (3) integrating ShellCheck into CI (GitHub Actions, Azure DevOps, pre-commit), (4) per-line and per-file disable directives (when justified), (5) shellcheck-rc and project configuration, (6) ShellCheck v0.11.0 new checks, (7) suppressing false positives correctly. Provides: ShellCheck install/CI setup, common warning catalog with fixes, CI workflow templates, and a quality gate pattern that fails builds on regressions.

Azure DevOps pipeline best practices, patterns, and industry standards. PROACTIVELY activate for: (1) authoring or reviewing Azure DevOps YAML pipelines, (2) multi-stage pipeline patterns (build, test, deploy), (3) reusable templates (steps, jobs, stages), (4) pipeline caching (Cache@2 task), (5) parallel jobs and matrix strategies, (6) deployment strategies (rolling, blue-green, canary), (7) approvals and environments, (8) variable groups, secret variables, Key Vault linkage, (9) service connections (Azure RM, GitHub, container registries), (10) pipeline versioning and pinning task major versions. Provides: YAML pattern catalog, template library structure, caching recipes, deployment strategy templates, and a pipeline-quality checklist.

Write comprehensive clinical reports including case reports (CARE guidelines), diagnostic reports (radiology/pathology/lab), clinical trial reports (ICH-E3, SAE, CSR), and patient documentation (SOAP, H&P, discharge summaries). Full support with templates, regulatory compliance (HIPAA, FDA, ICH-GCP), and validation tools.

Build authentication systems for TypeScript/Cloudflare Workers with social auth, 2FA, passkeys, organizations, and RBAC. Self-hosted alternative to Clerk/Auth.js. IMPORTANT: Requires Drizzle ORM or Kysely for D1 - no direct D1 adapter. v1.4.0 (Nov 2025) adds stateless sessions, ESM-only (breaking), JWT key rotation, SCIM provisioning. v1.3 adds SSO/SAML, multi-team support. Use when: self-hosting auth on Cloudflare D1, migrating from Clerk, implementing multi-tenant SaaS, or troubleshooting D1 adapter errors, session serialization, OAuth flows, TanStack Start cookie issues, nanostore session invalidation.

Build stateful Durable Objects for real-time apps, WebSocket servers, coordination, and persistent state. Use when: implementing chat rooms, multiplayer games, rate limiting, session management, WebSocket hibernation, or troubleshooting class export, migration, WebSocket state loss, or binding errors.

Create maintainer-friendly pull requests for open source projects with clean code submissions and professional communication. Prevents 16 common mistakes that cause PR rejection. Use when: contributing to public repositories, submitting PRs to community projects, migrating from contributor to maintainer workflows, or troubleshooting PR rejection, working on main branch errors, failing CI checks, or personal artifacts in commits.

Add headless Chrome automation with Puppeteer/Playwright on Cloudflare Workers. Use when: taking screenshots, generating PDFs, web scraping, crawling sites, browser automation, or troubleshooting XPath errors, browser timeouts, binding not passed errors, or session limits.

Build Model Context Protocol (MCP) servers on Cloudflare Workers - the only platform with official remote MCP support. TypeScript-based with OAuth, Durable Objects, and WebSocket hibernation. Use when: deploying remote MCP servers, implementing OAuth (GitHub/Google), using dual transports (SSE/HTTP), or troubleshooting URL path mismatches, McpAgent exports, OAuth redirects, CORS issues.

Build headless data tables with TanStack Table v8. Provides server-side pagination, filtering, sorting, and virtualization patterns for Cloudflare Workers + D1 databases. Use when building tables with large datasets, coordinating with TanStack Query, or troubleshooting state management issues, pagination coordination errors, or performance bottlenecks.

Build semantic search with Cloudflare Vectorize V2 (Sept 2024 GA). Covers V2 breaking changes: async mutations, 5M vectors/index (was 200K), 31ms latency (was 549ms), returnMetadata enum, and V1 deprecation (Dec 2024). Use when: migrating V1→V2, handling async mutations with mutationId, creating metadata indexes before insert, or troubleshooting "returnMetadata must be 'all'", V2 timing issues, metadata index errors, dimension mismatches.

Build async message queues with Cloudflare Queues for background processing. Use when: handling async tasks, batch processing, implementing retries, configuring dead letter queues, managing consumer concurrency, or troubleshooting queue timeout, batch retry, message loss, or throughput exceeded.

Store objects with R2's S3-compatible storage on Cloudflare's edge. Use when: uploading/downloading files, configuring CORS, generating presigned URLs, multipart uploads, managing metadata, or troubleshooting R2_ERROR, CORS failures, presigned URL issues, or quota errors.

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 serving APIs that require GPU acceleration or dynamic scaling.

Comprehensive DevOps skill for CI/CD, infrastructure automation, containerization, and cloud platforms (AWS, GCP, Azure). Includes pipeline setup, infrastructure as code, deployment automation, and monitoring. Use when setting up pipelines, deploying applications, managing infrastructure, implementing monitoring, or optimizing deployment processes.

Track ML experiments, manage model registry with versioning, deploy models to production, and reproduce experiments with MLflow - framework-agnostic ML lifecycle platform

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.

Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.

Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes deployments with continuous reconciliation. Use when implementing GitOps practices, automating Kubernetes deployments, or setting up declarative infrastructure management.

Implement Kubernetes security policies including NetworkPolicy, PodSecurityPolicy, and RBAC for production-grade security. Use when securing Kubernetes clusters, implementing network isolation, or enforcing pod security standards.

Build reusable Terraform modules for AWS, Azure, and GCP infrastructure following infrastructure-as-code best practices. Use when creating infrastructure modules, standardizing cloud provisioning, or implementing reusable IaC components.

Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.

Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.

Optimize cloud costs through resource rightsizing, tagging strategies, reserved instances, and spending analysis. Use when reducing cloud expenses, analyzing infrastructure costs, or implementing cost governance policies.

Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.

Configure secure, high-performance connectivity between on-premises infrastructure and cloud platforms using VPN and dedicated connections. Use when building hybrid cloud architectures, connecting data centers to cloud, or implementing secure cross-premises networking.

Project orientation for unfamiliar codebases. Use when entering a new project, exploring unknown repos, or working on shaky assumptions about build, test, lint, or CI setup.

Container development — Docker, multi-stage builds, Skaffold, non-root users, Alpine/slim images, security hardening. Use when working with Docker, Dockerfiles, docker-compose, or container security.

Set up automated CI fixing with Claude Code. Use when adding a workflow that analyzes failures, applies fixes, and files issues; pass --reusable for a multi-repo workflow_call template.

Analyze workflow runs — frequency, duration, success rates, efficiency. Use when investigating slow CI, high failure rates, or run patterns over time.

Terraform IaC: HCL, state management, modules, plan-apply workflows. Use when the user mentions Terraform, HCL, terraform plan/apply, tfstate, or IaC provisioning.

Kubernetes operations — deployment, management, troubleshooting, kubectl mastery. Use when the user mentions K8s, kubectl, pods, deployments, services, ingress, or cluster stability.

GitHub Actions CI/CD workflows for container builds, tests, releases. Use when updating outdated action versions, adding multi-platform builds, or auditing workflows.

FinOps metrics comparison across repos in an org. Use when benchmarking repos, identifying worst-performing ones, or doing org-wide CI cost analysis.

Identify GitHub Actions waste — skipped runs, bot triggers, missing concurrency — and suggest fixes. Use when CI costs are high or workflows run too often.

Integration testing: Supertest, pytest, Testcontainers. Use when setting up integration tests, creating docker-compose.test.yml, or separating from unit tests.

Load testing: k6, Artillery, Locust. Use when setting up load tests, auditing smoke/stress/spike/soak coverage, or adding CI performance regression detection.

GitHub Actions cache analysis — size, prefix/branch breakdown, stale detection. Use when investigating cache bloat, stale caches, or auditing cache key strategies.

Security scanning: dependency audits, SAST, secrets detection. Use when setting up Dependabot, CodeQL, or TruffleHog in CI, or creating a SECURITY.md policy.

Claude plugins marketplace setup: .claude/settings.json, GitHub Actions, plugin sets. Use when onboarding to claude-plugins, setting up claude.yml, or pinning plugins.

FinOps snapshot — org billing, workflow stats, cache usage. Use when you want a high-level view of CI spending or workflow health before diving deeper.

Container infrastructure: GHCR builds, Trivy/Grype scanning, devcontainer. Use when setting up multi-platform GHCR workflows or adding container scanning to CI.

Create, test, and package Helm charts — Chart.yaml, templates, dependencies, repo publishing. Use when the user mentions Helm charts, helm lint/template/package, or Kubernetes packaging.

Desktop application to back up all GitHub repositories locally and optionally to AWS S3 or Cloudflare R2 cloud storage

Manage Helm releases — install, upgrade, uninstall, list, inspect, history. Use when the user mentions deploying Helm charts, upgrading releases, or managing Kubernetes deployments.

Knip dead-code detector for JS/TS: unused files, deps, exports, types. Use when cleaning up codebases, finding dead exports, or enforcing dependency hygiene in CI.

Code docs: TSDoc, JSDoc, pydoc, rustdoc, TypeDoc, MkDocs, Sphinx. Use when setting up docstrings, configuring a docs generator, or enforcing doc coverage in CI.

Modern linters: Biome, Ruff, Clippy. Use when setting up linting, migrating ESLint/Prettier to Biome, or wiring lint into pre-commit and CI.

Personal AI assistant framework supporting multiple chat channels (DingTalk, Feishu, QQ, Discord, etc.) with extensible skills, local/cloud deployment, and cron scheduling.