Role design and levelling
Check an internal role definition against how the market defines and scopes the same role.
— Talent & Leadership
Researches how a role is defined externally and reshapes the findings into a structured benchmark you can hold your own definition against.
2–3 hours → ~8 minutes
Including the external research pass
No coding required
— USE CASES
Check an internal role definition against how the market defines and scopes the same role.
Set expectations for a hire using an external reference rather than an internal precedent.
Feed structured external benchmarks into a framework or levelling exercise.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
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.
Content is restructured into the form your deliverable or downstream system expects, with each role kept intact.
In talent & leadership work, role benchmark research is one of those tasks that looks straightforward until you are three documents deep and the details stop agreeing with each other. Role design and levelling is the typical trigger — check an internal role definition against how the market defines and scopes the same role. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 2–3 hours of manual work.
Skillsize turns that work into a Skill: you supply the material, and what comes back is a structured external role benchmark, with findings reshaped for direct comparison. What sits between input and output is the codified method: thresholds, sequencing and the points where a human confirms a call — all of it visible and editable in the Skill. In effect, 2–3 hours of senior time compresses into ~8 minutes — and the output is comparable across clients, quarters and colleagues instead of shaped by whoever ran it.
Role benchmark research 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.
Builds evidence-backed employee skills profiles within HR systems, mapping documented experience to the organisation’s skills catalogue and assigning proficiency levels using consistent rules.
Assesses how clearly people explain their technical work against a consistent four-level rubric, producing a human-approved report with quoted evidence behind every score.
Reveals how organisational culture is lived through anonymous employee accounts, producing an evidence-backed diagnostic of shared themes, differences between functions and gaps between values and practice.
Turns a high-potential's assessment evidence into an acceleration plan weighted to real experience and exposure, naming the stretch assignments, mentors and programmes that will compound fastest.
Builds a calibrated, reusable benchmark from source material so every later screen, shortlist or review is graded against the same bar.
Screens candidate evidence against a saved Blueprint, applying the same calibrated bar and traceable reasoning to every applicant.