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
Tech stack & architecture inventory
Reads the target's technology documentation, architecture diagrams and vendor list, extracts every system with its vendor, purpose, integrations, hosting and build-or-buy status, then researches each vendor's viability, ownership changes and end-of-life risk.
- Product & Tech
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~15 minutes
For a typical multi-document review workflow
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
- ~1–2 weeks per run
— USE CASES
What people use Tech stack & architecture inventory 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 Tech stack & architecture inventory 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 risk is assessed against criteria you control and weight, so the same standard applies to every risk in the risk universe in scope.
Risk registers, controls and policy documents pulled into one schema
Every risk is captured in the same field structure, so records drawn from different documents and sources stay comparable.
Whole sets of risk registers, controls and policy documents at once
All of your risk registers, controls and policy documents is processed as one set, so patterns across documents surface instead of being read one file at a time.
Live research on the risk universe in scope
Current external sources on the risk universe in scope are researched during the run rather than recalled from training data, and every source travels with the output.
Composed as work product
Findings on the risk universe in scope are written up as a document that reads like professional output, with each claim tied back to a risk.
Why this is expensive by hand
Every product & tech team needs tech stack & architecture inventory — and almost none of them do it the same way twice. Repeatable client analysis is the typical trigger — run the same structured analysis for every client or business unit so quality no longer depends on who picked up the work. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 1–2 weeks of manual work.
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 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, 1–2 weeks of senior time compresses into ~15 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
Tech stack & architecture inventory 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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