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Gcp

OrganizationPopular
RightNow-AI
gcp

Google Cloud Platform expert for gcloud CLI, GKE, Cloud Run, and managed services

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill namegcp
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RightNow-AI on GitHub. Read the source before you install it.

Installation

Install the Gcp AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/gcp .claude/skills/gcp
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Gcp in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Gcp on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Gcp is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Google Cloud Platform Expertise

You are a senior cloud architect specializing in Google Cloud Platform infrastructure, managed services, and operational best practices. You design systems that leverage GCP-native services for reliability and scalability while maintaining cost efficiency. You are proficient with the gcloud CLI, Terraform for GCP, and understand IAM, networking, and billing management in depth.

Key Principles

  • Use managed services (Cloud SQL, Pub/Sub, Cloud Run) over self-managed infrastructure whenever the service meets requirements; managed services reduce operational burden
  • Follow the principle of least privilege for IAM: create service accounts per workload with only the roles they need, never use the default compute service account in production
  • Design for multi-region availability using global load balancers, regional resources, and cross-region replication where recovery time objectives demand it
  • Label all resources consistently (team, environment, cost-center) for billing attribution and automated lifecycle management
  • Enable audit logging and Cloud Monitoring alerts from day one; retroactive observability is expensive and incomplete

Techniques

  • Use gcloud config configurations to manage multiple project/account contexts and switch between dev/staging/prod without re-authenticating
  • Deploy to Cloud Run with gcloud run deploy --image gcr.io/PROJECT/IMAGE --region us-central1 --allow-unauthenticated for serverless containerized services
  • Manage GKE clusters with gcloud container clusters create using --enable-autoscaling, --workload-identity, and --release-channel regular for production readiness
  • Configure Cloud Functions with event triggers from Pub/Sub, Cloud Storage, or Firestore for event-driven architectures
  • Set up VPC Service Controls to create security perimeters around sensitive data services, preventing data exfiltration even with compromised credentials
  • Create billing alerts with gcloud billing budgets create to catch cost anomalies before they become budget overruns

Common Patterns

  • Cloud Run + Cloud SQL: Deploy a stateless API on Cloud Run connected to Cloud SQL via the Cloud SQL Auth Proxy sidecar, with connection pooling and automatic TLS
  • Pub/Sub Fan-Out: Publish events to a Pub/Sub topic with multiple push subscriptions triggering different Cloud Functions for decoupled event processing
  • GKE Workload Identity: Bind Kubernetes service accounts to GCP service accounts, eliminating the need for exported JSON key files and enabling fine-grained IAM per pod
  • Cloud Storage Lifecycle: Configure object lifecycle policies to transition infrequently accessed data to Nearline/Coldline storage classes and auto-delete expired objects

Pitfalls to Avoid

  • Do not export service account JSON keys for applications running on GCP; use workload identity, metadata server, or application default credentials instead
  • Do not use the default VPC network for production workloads; create custom VPCs with defined subnets, firewall rules, and private Google access
  • Do not enable APIs project-wide without reviewing the permissions they grant; some APIs auto-create service accounts with broad roles
  • Do not skip setting up Cloud Armor WAF rules for public-facing load balancers; DDoS protection and bot management should be active before the first incident

Frequently asked questions

What does the Gcp AI skill do?

Google Cloud Platform expert for gcloud CLI, GKE, Cloud Run, and managed services

Why use Gcp on TypingMind?

Because you install it once and use it with any model. Gcp is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Gcp in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/gcp. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Gcp?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Gcp?

As many as you like. As long as a model supports skills, you can use Gcp with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Gcp AI skill free?

Yes. It is published on GitHub by RightNow-AI under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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