Google Professional Cloud Architect Skill

A full adaptive coaching system for the Google Professional Cloud Architect exam, packaged as a Claude Skill. Unlike a one-shot study plan, the skill runs real coaching sessions, tracks your weak spots across conversations, and tells you when you are genuinely ready to sit the exam.

What the skill does

• Two-phase coaching. Phase 1 builds coverage across all five PCA domains (Cloud Solution Architecture, Technical & Business Processes, Solution Design, Infrastructure Implementation, Reliability & Security). Phase 2 mirrors the real exam — tighter constraints, harder trade-offs, higher bar.
• Scenario-based sessions with 150–250 word business contexts, explicit constraints (regulatory, latency, cost, staffing, timelines), and your role clearly stated.
• Rubric scoring on six axes — Service Selection, Scalability, Reliability/HA, Security & IAM, Cost Optimization, Operational Model — so you see exactly where your design is weak, not just whether it was wrong.
• Spaced repetition. Services you keep forgetting (PSC vs. VPC peering, Spanner vs. Firestore, Dataflow vs. Dataproc) get re-surfaced in later scenarios in disguised form.
• A mnemonic for every mistake. Compute picker, storage picker, database picker, networking picker — wrong answers always come with a memory trick you can recall under exam pressure.
• Official case-study drills. EHR Healthcare, Helicopter Racing League, Mountkirk Games, TerramEarth — the skill simulates PCA-style questions against each.
• HTML progress tracker. After every session the skill generates a standalone HTML file with a mastery gauge, per-domain progress bars, weak-topic chips, a session history strip, and an "EXAM READY" banner when thresholds are hit.
• Readiness signal. The skill declares you exam-ready when all domains reach 70% and you score 85%+ on 3 consecutive Phase 2 sessions — no guessing.

How it works

1. Intake — on first run the skill introduces itself, asks your level (beginner / intermediate / advanced), background, known weak areas, and target exam date.
2. Per-session loop — one scenario at a time. You post your design, the skill scores it 0–5 on all six axes, produces the model answer with specific GCP services, lists what you missed, and asks one "what would change if…" follow-up that flips a constraint.
3. End-of-session artifacts — a summary table, a running scores table, the HTML progress tracker, and a phase-transition check.
4. Phase 2 flip — when all domains are ≥ 70% and your 3-session average is ≥ 75%, Phase 2 starts automatically. Harder trade-offs, tighter budgets, multi-region and hybrid-cloud curveballs, higher bar (85%+ × 3 in a row).
5. Continuity across sessions — the skill reads prior conversation state, so your weak spots, case-study coverage, and coaching persona carry forward without you having to restate them.

How to use it

1. Click ⬇ Download this Claude Skill above.
2. Import the .md file — either through Claude Desktop (Customize → Skills → + → Create skill → Upload a skill) or by dropping it into .claude/commands/ or ~/.claude/commands/ for Claude Code. Full walkthrough in the import tutorial.
3. Invoke the skill:

   /google-cloud-architect
   

   or pass your level up front:

   /google-cloud-architect intermediate, 3 years on AWS migrating to GCP
   

4. Run a session. Come back tomorrow, next week, or a month later — the coaching picks up where you left off.

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Quick-start prompt (no download)

Prefer a one-shot scenario simulator without installing anything? Paste this into Claude:

Act as a Google Cloud-certified instructor running a PCA exam simulator. Do not produce all scenarios at once — loop through them one at a time.

For each scenario:

1. Present one 150–250 word scenario that includes business context, current architecture, explicit constraints (regulatory, latency, cost, staffing, timelines), success criteria, and my role.
2. Wait for my proposed design before revealing anything.
3. Score my response 0–5 on six axes (Service Selection, Scalability, Reliability/HA, Security & IAM, Cost Optimization, Operational Model) as a table.
4. Give the model answer naming specific current GCP services and the trade-offs.
5. List every GCP service I missed that would have improved the design, with a one-line reason.
6. Ask one "what would change if…" follow-up that flips a constraint.

Over 5 scenarios, collectively cover: on-prem migration (Compute Engine vs. GKE vs. Cloud Run vs. App Engine), data analytics at scale (Pub/Sub, Dataflow, Dataproc, BigQuery, Bigtable), hybrid/multi-cloud networking (VPN, Interconnect, Shared VPC, PSC, VPC-SC), a regulated industry with data residency and CMEK, and a global low-latency consumer app (Cloud LB, CDN, Spanner vs. Firestore, Memorystore).

On request, produce decision-matrix tables: compute picker, storage picker, database picker, networking picker. Support case-study reviews of EHR Healthcare, Helicopter Racing League, Mountkirk Games, and TerramEarth on request.

Tips:

• The downloadable skill is the better path if you have more than one study session planned — it's the difference between a static simulator and a coach that remembers you.
• If you propose a service that technically works but is over-engineered or over-priced, the skill scores it down and explains the lighter alternative.
• For every recommendation, force yourself to cite the constraint it satisfies ("I chose Spanner because the scenario requires strong global consistency").
• Review all 4 published case studies before exam day — they're the closest thing to leaked questions.

⚠ This skill has been tested and optimized for Claude. Results may vary with other AI assistants.