Loading...
Loading...
Found 35 Skills
Sets up and configures Google Kubernetes Engine (GKE) clusters for production use. Use when creating new GKE clusters, choosing between Autopilot vs Standard modes, configuring networking (VPC-native, private clusters), setting up node pools, or planning cluster architecture for Spring Boot microservices. Includes regional vs zonal decisions, security hardening, and resource provisioning guidance.
Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.
Accept a vague instruction, automatically conduct investigation, classification, break it down into XML phase plans, select skills, define completion criteria, then execute it fully in unattended mode via loop/goal + agent-mode — including automatic deployment, automatic E2E testing, automatic code review, without skipping any phases. Activate proactively when the user provides a broad task — such as "fix the bug", "add tests", "optimize performance", "finish this feature", "scan the code", "investigate why XX happens". It also triggers when the user says "autopilot", "auto", "help me plan", "handle it yourself", "run directly", "break it down for me", "don't ask me how to do it". Even if the user doesn't use these keywords, it should activate proactively if the input is clearly an unbroken broad intent. Calling autopilot = authorizing fully automatic unattended execution, no mid-process confirmation required.
End-to-end autopilot orchestrator for setting up Microsoft Teams integration in Salesforce Service Cloud ITSM — runs the whole flow (enable the Teams for Employee Service Go feature, register the Microsoft Entra app, populate Named Credentials, configure the IT Desk and IT Service checklists, turn on Swarming, and optionally embed the Agentforce agent) in one continuous pass, stopping only at the points a human must act. Use when the user asks to set up Microsoft Teams for ITSM end to end, 'set up teams for it service', 'do the whole teams itsm setup', 'configure microsoft teams for employee service', or wants a guided Teams ITSM walkthrough. Delegates each stage to a specialized child skill while driving the sequence itself. DO NOT TRIGGER when the user asks to enable Teams alone, configure just the IT Desk or IT Service checklist alone, or enable Swarming alone — delegate directly to the specific child skill in those cases.
FORGE Autopilot — Intelligent autonomous mode. FORGE analyzes the project state, automatically decides the next action, and orchestrates all agents until completion. Configurable checkpoints for human review. Usage: /forge-auto or /forge-auto "specific objective"
Configure LaunchDarkly Release Autopilot settings (GitHub App auto-flagging and auto-releasing) via the hosted MCP, or diagnose why a pull request was not classified / auto-flagged. Use when the user wants to turn on auto-flagging, map a GitHub repo to a LaunchDarkly project, change Release Autopilot account defaults, unmap a repo, or asks why Release Autopilot did not classify their PR.
Use when the developer wants the agent to work without approving every write - "tu dong hoan toan", "cu lam het di", "dung hoi tung buoc", "work autonomously", "approve everything for this task", a long build session - or when an apply preview says autopilot is active, paused, expired or not covering a statement. Requests one developer-approved lease, works strictly inside it, stops where it stops, and reports every write it made.
When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.
Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead).
Generates and updates secure, production-ready Kubernetes YAML manifests optimized for GKE Autopilot and GKE Standard clusters. Use when creating or modifying GKE deployment manifests, configuring container security contexts, setting CPU/memory resource limits, defining readiness/liveness/startup probes, mounting secrets and volumes, configuring GKE Gateway API routes, targeting Spot VMs, or deploying AI model inference workloads (vLLM, TGI, Gemma). Don't use for live cluster operations, pod troubleshooting (use gke-workload-troubleshooting), or cluster infrastructure provisioning (use gke-cluster-creation).
Shadow platform help — bot-free AI meeting assistant capturing audio + screen on macOS, on-device transcription, autopilot meeting detection, AI summaries/action items/follow-up emails, Skills system for custom post-meeting tasks. Use when setting up Shadow for the first time, Shadow not detecting meetings automatically, Shadow using too much CPU or memory on Mac, Shadow speaker attribution is wrong, Shadow screen capture not working, Shadow free tier ran out of AI meetings, choosing between Shadow and Granola or Jamie or Bluedot for bot-free recording, or exporting Shadow notes to Markdown or Zapier. Do NOT use for choosing between all AI note-takers (use /sales-note-taker) or reviewing a call for coaching (use /sales-call-review).
One-shot autopilot orchestrator — runs the full spark-video pipeline (screenwriter ↔ director per-scene parallel → render chain-DAG parallel + per-clip review → stitch). User confirms at 4 gates (+ 1 mode gate at start + 1 BGM gate when bgm/ folder detected). Use when the user wants "make me an episode" in one command.