Repeatable client analysis
Run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work.
— Product & Tech
Scalability & infrastructure stress test
Takes traffic and load data, infrastructure cost data, the architecture document and SLA/uptime history. Extracts throughput, latency, cost-per-transaction and peak load, groups usage by service, computes a headroom ratio against documented capacity, and projects what fails first at 2× and 5× scale.
- Product & Tech
- Deterministic scoring
- Traceable reasoning
- Runs anywhere
2–3 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- Documents, exports or uploads you already hold
- Output
- A structured, review-ready deliverable
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2–3 weeks per run
— USE CASES
What people use Scalability & infrastructure stress test for
Faster first drafts
Turn raw source material into a working draft in minutes and spend your time on judgement instead of assembly.
Comparable results over time
Produce the same shape of output each cycle so movement is measurable rather than re-argued.
What it works from
- Documents, exports or uploads you already hold
- Your own criteria, framework or house method
What you get back
- A structured, review-ready deliverable
- A traceable record of what informed each conclusion
— HOW IT BEHAVES
How Scalability & infrastructure stress test 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 role is assessed against criteria you control and weight, so the same standard applies to every role in the organisation in scope.
Calculated per role, not estimated
The figures behind each role are computed by formula during the run, so the arithmetic is identical every time and can be checked line by line.
Numbers lifted out of org data, role documentation and headcount exports
Figures buried in narrative org data, role documentation and headcount exports are extracted as data you can compute and compare with.
Live research on the organisation in scope
Current external sources on the organisation in scope are researched during the run rather than recalled from training data, and every source travels with the output.
Every row of the organisation in scope
Each row of your export is processed on the same basis, so no role is skipped however long the table is.
The pattern charted
Movement across the organisation in scope is visualised from the computed data, so the trend is legible at a glance.
Why this is expensive by hand
Every product & tech team needs scalability & infrastructure stress test — and almost none of them do it the same way twice. In practice it shows up as repeatable client analysis: run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work. 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 a structured, review-ready deliverable, with a traceable record of what informed each conclusion. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. 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
Scalability & infrastructure stress test 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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