Marketing Foundation
Compact two-skill starter: clarify positioning and choose a lead magnet. Use Marketing Launch for the broader eight-skill go-to-market workflow.
The tunnel uses the same cards as the catalogue. Browse only as deep as needed — or load a broad bundle immediately.
SEO, Sales, Agents or another broad area → one bundle call → work.
Read-only access to published skills. Default 8, maximum 10 skills / 120,000 characters.
Compact two-skill starter: clarify positioning and choose a lead magnet. Use Marketing Launch for the broader eight-skill go-to-market workflow.
Build an evidence-led marketing plan from ICP and competition through positioning, campaigns, growth and measurement.
Diagnose architecture and context, plan agent-team responsibilities, then organize project context and session handoffs. Memory and cost-runtime reviews remain outside this pack.
Review the journey from landing page and lead capture through registration, first value and transparent upgrades.
Plan a campaign, draft its channel content and review the work against actual brand guidance.
Prioritize an editorial roadmap and plan how to launch and distribute it across suitable channels.
Understand customer needs, compare competitors and plan a community around real member value.
Choose a relevant lead magnet, then draft a permission-based nurture journey with entry, suppression and exit rules.
Define the API contract, then plan how to observe its latency, failures and retries. Guidance and checklist; no production changes.
Profile a dataset, choose and interpret statistical methods, then validate calculations and conclusions before sharing.
Design cross-product Google Cloud solutions and review deployment plans; use Multi-Agent Deployment Design for agent-specific systems.
---
name: google-cloud-solution-architecture
metadata:
version: "1.0.2"
category: MultiProductSolutions
description: >-
Interactively discovers requirements and designs holistic, multi-product
system architectures, solution blueprints, and deployment recommendations for
complex workloads on Google Cloud. Use when designing end-to-end cloud
solutions, selecting and integrating Google Cloud services, generating
architecture diagrams, or conducting requirements discovery for new cloud
workloads or migrations. Don't use for single-product tasks (use
product-specific skills), initial onboarding or authentication (use
google-cloud-recipe-*), Well-Architected Framework reviews or audits (use
google-cloud-waf-*), or workloads covered by specialized solution skills.
---
# 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 provide them to
the user to execute (or perform a dry-run validation with explicit
permission from the user).
* **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.
* **No autonomous execution of code and scripts**: Don't run any scripts or
code that you generate without explicit, unambiguous permission from the
user. Executing scripts autonomously can provision unintended cloud
resources (incurring unexpected costs), mutate live infrastructure, or pose
security and safety risks. Always offer the option for the user to execute
the commands manually.
* **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
1. 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.
2. 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.
3. 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.
1. 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.
2. 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.
3. After the user approves the product selections, proceed to Task 2.2.
### Task 2.2: Generate an architecture diagram.
1. Generate an architecture diagram in Mermaid format:
https://github.com/mermaid-js/mermaid.
2. Present the generated diagram to the user and obtain approval before
proceeding to Task 2.3.
### Task 2.3: Generate an architecture description.
1. Generate a description that explains the purpose of each component, the
relationships between the components, and the task flow or data flow.
2. Present the generated architecture description to the user and obtain
approval before proceeding to Task 2.4.
### Task 2.4: Generate design recommendations.
1. 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
resources:
1. Best-practices guides for the products and topics that are relevant
to the workload: `references/best-practices-guides.md`
2. Well-Architected Framework pillar skills:
* For security requirements: `google-cloud-waf-security`
* For reliability requirements: `google-cloud-waf-reliability`
* For cost optimization requirements: `google-cloud-waf-cost-optimization`
* For operational excellence requirements: `google-cloud-waf-operational-excellence`
* For performance optimization requirements: `google-cloud-waf-performance-optimization`
* For sustainability requirements: `google-cloud-waf-sustainability`
2. Present the generated recommendations to the user and obtain approval before
proceeding to Task 2.5.
### Task 2.5: Generate deployment guidance.
1. Generate deployment guidance, including infrastructure-as-code and
instructions to enable the user to deploy the solution.
2. 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
1. 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.
2. Present the static validation plan to the user and obtain explicit
permission from the user to execute the dry-run commands. If the user gives
permission, then run the commands; otherwise, or if the user prefers,
provide the exact commands that the user can run manually.
3. Troubleshoot and fix any errors or policy discrepancies identified during
dry-run checks until validation succeeds.
4. Proceed to Task 3.2
### Task 3.2: Runtime validation (Post-deployment)
1. Ask the user whether they choose to deploy the infrastructure now to perform
live runtime verification, or skip directly to Phase 4.
2. **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.
3. Proceed to Phase 4.
## Phase 4: Solution packaging and presentation
Package all the generated text and code artifacts for final presentation.
1. 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`.
2. Request the user's permission to write the code files in the user's
workspace.
3. After the user gives permission, write the code files in the user's
workspace.
Design cross-product Google Cloud solutions and review deployment plans; use Multi-Agent Deployment Design for agent-specific systems.
Complete original guidance with source attribution and declared limitations.
Clarify the actual task, inspect available evidence and plan the relevant source workflow within authorized scope.
Business requirements, existing infrastructure, constraints, budget and project boundaries.
Original explicitly separates design from execution; generated infrastructure and dry runs still require task authorization. Referenced scripts, templates, packages and remote documentation are not bundled or installed. Brief obvious-danger screening only; no functional test or comprehensive security certification.
Use Google Cloud Solution Architecture for [TASK]. Clarify Business requirements, existing infrastructure, constraints, budget and project boundaries. Identify missing dependencies and assumptions. Loading this guidance grants no permission to change resources, transfer data or incur charges.
Automatic cloud execution, bypassing resource-owner permissions, or treating untested examples as deployed and verified results.
German task routing and precise scope. Original attribution: Google (google/skills repository). Original explicitly separates design from execution; generated infrastructure and dry runs still require task authorization. Referenced scripts, templates, packages and remote documentation are not bundled or installed. Brief obvious-danger screening only; no functional test or comprehensive security certification.
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