Preparing for product growth
Identifies architectural constraints that could limit scale or availability as demand grows. Provides evidence-backed priorities for addressing capacity and resilience risks.
— Product & Tech
Technical architecture review
Reviews a system's architecture documentation for scalability limits, resilience gaps, security weaknesses and accumulated technical debt, then returns a prioritised remediation plan showing what to fix first and why it matters.
- Product & Tech
- Traceable reasoning
- Runs anywhere
2–3 weeks → ~25 minutes
For a typical multi-document review workflow
No coding required
- Input
- Technical architecture documentation
- Output
- Technical architecture diagnostic report
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2–3 weeks per run
— USE CASES
What people use Technical architecture review for
Reviewing recurring service incidents
Assesses architecture alongside incident and performance evidence to highlight weaknesses in resilience and availability. Distinguishes targeted fixes from issues requiring structural change.
Assessing security by design
Examines documented design decisions and component relationships for security weaknesses. Ties findings to evidence and rates severity and remediation effort to support prioritisation.
Planning technical debt investment
Makes accumulated architectural debt explicit and connects it to affected components. Provides a prioritised remediation plan that separates quick wins from larger engineering commitments.
What it works from
- Technical architecture documentation
- System and component diagrams
- Design decisions and architectural rationale
- Incident reports and service reliability evidence, where available, for the architecture under review to substantiate resilience findings and remediation priorities
What you get back
- Technical architecture diagnostic report
- Findings across scalability, resilience and availability, security by design, and technical debt
- Component-level findings linked to supporting evidence
- Severity and remediation effort ratings for each finding to support prioritisation and make trade-offs clear across affected components and architectural concerns and investment discussions with stakeholders
— HOW IT BEHAVES
How Technical architecture review produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Scored against your criteria
Each decision is assessed against criteria you control and weight, so the same standard applies to every decision in the decision set in scope.
Governance and authority documentation pulled into one schema
Every decision is captured in the same field structure, so records drawn from different documents and sources stay comparable.
Whole sets of governance and authority documentation at once
All of your governance and authority documentation is processed as one set, so patterns across documents surface instead of being read one file at a time.
Composed as work product
Findings on the decision set in scope are written up as a document that reads like professional output, with each claim tied back to a decision.
Why this is expensive by hand
Architecture reviews often leave advisory teams with fragmented evidence, competing technical concerns and recommendations that are difficult to prioritise. In practice it shows up as preparing for product growth: identifies architectural constraints that could limit scale or availability as demand grows. Provides evidence-backed priorities for addressing capacity and resilience risks. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 2–3 weeks of capacity for it.
How this Skill produces it
Skillsize turns that work into a Skill: you supply the material, and what comes back is technical architecture diagnostic report, with findings across scalability, resilience and availability, security by design, and technical debt. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. In effect, 2–3 weeks of senior time compresses into ~25 minutes — and the output is comparable across clients, quarters and colleagues instead of shaped by whoever ran it.
Who it's for
- Independent consultants codifying their own methodology
- Strategy and transformation teams standardising delivery
- Internal advisory functions under pressure to produce faster
- Operators who need defensible output, not a one-off chat answer
Run it in Skillsize — or export it anywhere
Technical architecture review exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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Security & compliance posture scan
Assesses security controls and supporting evidence against relevant compliance frameworks, producing a risk-led remediation plan or an assurance summary grounded in documented findings.
Product & Tech
Scalability & infrastructure stress test
Assesses infrastructure headroom against documented peak demand, projects the first constraints at 2× and 5× load, and identifies the bottleneck to prioritise before growth puts service reliability at risk.
Product & Tech
Product roadmap realism check
Tests product roadmap commitments against engineering capacity, delivery history and dependencies to give investment committees a defensible view of what is likely to ship within twelve months.