mcpbeat

Google Cloud Solution Architecture

google/google-cloud-solution-architecture

>- Interactively discovers requirements for a specific cloud workload and generates design recommendations and architectural guidance to build a multi-product solution in Google Cloud. Use this skill for holistic, end-to-end design recommendations and architectural guidance for complex, multi-product workloads on Google Cloud for specific use cases. Don't use this skill when other specialized skills (e.g., product-specific or google-cloud-recipe-*) directly address the user's workload or use case.

33k tokens
context cost
the whole folder, loaded on every use
5
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instructions only
0
copies elsewhere
how many repositories repackaged it
15506
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/google/skills --skill google-cloud-solution-architecture

What comes with it

118 909 bytes besides the instruction
assets/output-template.md
references/architecture-guides.md
references/best-practices-guides.md
references/decision-making-guides.md

The instruction itself

14 sections, as written by the author

Google Cloud solution-architecture workflow

Overview of the workflow

The workflow consists of the following phases:

  • Phase 1: Requirements discovery. Gather detailed requirements related to

the cloud workload or use case that the user needs assistance for.

  • Phase 2: Solution architecture. Use the requirements that were gathered

in Phase 1 to generate a detailed solution architecture for the cloud

workload or use case.

  • Phase 3: Solution validation. Create a plan to validate the generated

solution, generate validation instructions and scripts, and run the

validation.

  • Phase 4: Solution packing and presentation. Consolidate the generated

content and present the solution.

Important notes about the workflow:

  • Strict phase separation: During Phase 1 (Requirements discovery), when

you ask the user clarifying questions, don't recommend, propose, or outline

any architectural designs, technical decompositions, cloud services, or

component mappings. Proposing solutions before functional and non-functional

requirements are thoroughly assessed causes confirmation bias and risks

anchoring the solution on specific products, features, or tools prematurely.

  • Iterative approval & task transitions: For each deliverable in this

workflow (technical decompositions, product recommendations, diagrams,

architectural descriptions, and deployment scripts), explicitly present your

output to the user for approval. If the user requests modifications,

iteratively revise the content until approved before progressing to the

subsequent task or phase.

  • When you can skip certain phases: If the user's prompt indicates that a

specific phase or task in this workflow is already completed or approved

(e.g., "requirements discovery stage is completed", "product selection is

approved", or "architecture is confirmed"), don't repeat that phase or task.

Instead, skip directly to the requested task (such as generating the

technical decomposition, recommending products, or compiling the solution

guide).

Phase 1: Requirements discovery

  • Gather the following requirements related to the workload or use case for

which the user needs assistance.

CRITICAL: You MUST NOT generate any architecture designs,

product recommendations, or technical decompositions until the user provides

these requirements.

  • Functional requirements: Ask the user to describe the business processes,

activities, and use cases of their workload.

  • Non-functional requirements: Ask the user to describe requirements for

security, privacy, compliance, reliability, disaster recovery, cost,

operations, performance, and sustainability.

  • CRITICAL: If non-functional requirements are missing or incomplete,

you MUST ask the user to describe the requirements and explicitly explain

why they are important (e.g., because they directly dictate operational

SLAs, availability tiers, scaling configuration, cost budgets, resource

types, and the security posture) when asking the user to supply them.

  • Current state: Ask whether the workload currently runs

on other cloud providers or on-premises (if yes, prompt for the architecture

of the existing deployment).

  • System dependencies: Ask the user to describe any dependencies between

their application and other workloads, products, systems, or tools.

  • Review the input that the user has provided so far, and check whether there

are any ambiguities or contradictions (e.g., conflicting goals like complete

network isolation with zero internet exposure vs. real-time ingestion from

public APIs).

If you identify any ambiguities or contradictions in the user's requirements,

you must:

  • Clearly describe the ambiguities and contradictions.
  • Explain why the contradictory requirements cannot be simultaneously

satisfied.

  • Request the user to clarify their trade-off preferences and choices to

resolve the ambiguities and contradictions.

  • If the user delegates the choice to you (e.g., the user replies with

"do what you think is best" or "you decide"), then provide a clear

suggestion to resolve the ambiguity or contradiction, explain your

reasoning, and ask the user to approve your suggestion.

CRITICAL: Until all the ambiguities and contradictions that you identify

are resolved, don't recommend or generate any architecture design, technical

decomposition, or Google Cloud product recommendations. Ambiguous or

contradictory requirements lead to invalid architectural assumptions.

  • Generate a technical decomposition of the components of the workload that

breaks down the solution into logical components. Present it to the user and

obtain approval before proceeding to Phase 2.

CRITICAL: Before proceeding to Phase 2, ensure that the user has

approved the technical decomposition. Misalignment of the technical

decomposition with the user's requirements will invalidate the outputs of the

subsequent phases in this workflow.

Phase 2: Solution architecture

Use the approved requirements from Phase 1 to generate a comprehensive solution

architecture.

Ground all generated content

For each task in this phase, to ensure that the generated content aligns with

the latest and official Google Cloud guidance, you must ground the generated

content by using the following resources:

  • Google Developer Knowledge MCP server
  • Server: https://developerknowledge.googleapis.com/mcp
  • Tools:
  • developerknowledge:search_documents
  • developerknowledge:get_documents
  • developerknowledge:answer_query
  • Relevant skills from https://github.com/google/skills
  • Official Google Cloud documentation, including the following:
  • Reference architectures and design guides that are relevant to the

technology category of the workload: references/architecture-guides.md

  • Decision-making guides for the products and topics that are relevant to

the workload: references/decision-making-guides.md

  • Best-practices guides for the products and topics that are relevant to

the workload: references/best-practices-guides.md

For each item in the generated guidance, you must include citations to the

relevant official Google Cloud documentation pages.

Task 2.1: Identify Google Cloud products and features required for the workload.

  • Recommend the products and features that are appropriate for each component

of the user's workload.

CRITICAL:

  • Don't recommend any products or features that are deprecated, retired,

decommissioned, or unsupported. To check the status of a product or

feature, call developerknowledge:answer_query or

developerknowledge:search_documents with query strings like:

"{product_name} release status".

  • If multiple products or features can be used for a component of the

workload, then do the following:

  • Recommend the most appropriate product or feature. When alternative

products exist, the relevant product documentation might provide guidance

on when to choose each product. Follow that guidance.

  • Mention the available alternative products or features.
  • Explain the pros and cons of each alternative product or feature.
  • Present the generated product recommendations to the user and ask whether any

changes are needed.

CRITICAL: Don't generate anything further (architecture diagrams,

descriptions, or deployment configurations) in the same turn. Halt execution

immediately after listing the product choices until the user approves the

product selections.

  • After the user approves the product selections, proceed to Task 2.2.

Task 2.2: Generate an architecture diagram.

  • Generate an architecture diagram in Mermaid format: https://github.com/mermaid-js/mermaid.
  • Present the generated diagram to the user and obtain approval before

proceeding to Task 2.3.

Task 2.3: Generate an architecture description.

  • Generate a description that explains the purpose of each component, the

relationships between the components, and the task flow or data flow.

  • Present the generated architecture description to the user and obtain

approval before proceeding to Task 2.4.

Task 2.4: Generate design recommendations.

  • Generate design recommendations and best practices to optimally configure

each component in the architecture based on the workload's requirements.

Important:

  • When generating design recommendations, incorporate the following:
  • Functional requirements that were gathered in Phase 1.
  • Non-functional requirements that were gathered in Phase 1.
  • To generate guidance for non-functional requirements, use the following

skills, as appropriate:

  • google-cloud-waf-security
  • google-cloud-waf-reliability
  • google-cloud-waf-cost-optimization
  • google-cloud-waf-operational-excellence
  • google-cloud-waf-performance-optimization
  • google-cloud-waf-sustainability

If any of the specialized google-cloud-waf-* skills are not available in

your current workspace, derive design guidance directly from the

documentation references in references/best-practices-guides.md.

  • Present the generated recommendations to the user and obtain approval before

proceeding to Task 2.5.

Task 2.5: Generate deployment guidance.

  • Generate deployment guidance, including infrastructure-as-code and

instructions to enable the user to deploy the solution.

  • Present the generated deployment guidance to the user and obtain approval

before proceeding to Phase 3.

Phase 3: Solution validation

Task 3.1: Pre-deployment validation

  • Create a pre-deployment plan to statically validate the generated solution

and verify that it meets the workload's requirements without provisioning

live resources:

  • Deployment dry-run: Validate infrastructure syntax and preview the

resources that will be provisioned using dry-run commands (e.g.,

terraform plan or (where supported) gcloud ... --dry-run).

  • Architecture & policy analysis: Perform static verification of

network routing topologies, firewall rules, and IAM enforcement against

best practices.

  • Present the static validation plan to the user, obtain approval, and execute

the dry-run commands.

  • Troubleshoot and fix any errors or policy discrepancies identified during

dry-run checks until validation succeeds.

  • Proceed to Task 3.2

Task 3.2: Runtime validation (Post-deployment)

  • Ask the user whether they choose to deploy the infrastructure now to perform

live runtime verification, or skip directly to Phase 4.

  • If the user chooses to deploy the infrastructure:
  • After the user deploys the infrastructure, generate runtime

verification commands (using tools like curl, ping, or gcloud)

and provide them to the user to execute, to test live endpoint

reachability, networking paths, and load balancer routing.

  • Troubleshoot any deployment or runtime routing issues until checks pass.
  • Proceed to Phase 4.

Phase 4: Solution packaging and presentation

Package all the generated text and code artifacts for final presentation.

  • Consolidate the text artifacts that were generated in Phase 2 and Phase 3

into a single Markdown file named solution-architecture-guide.md, based on

the template in assets/output-template.md.

  • Request the user's permission to write the code files in the user's

workspace.

  • After the user gives permission, write the code files in the user's

workspace.

How to use it

Copy the folder

Take google/google-cloud-solution-architecture from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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