Codifying a hiring bar
Turn the evidence from your best performers into a benchmark future candidates are screened against.
— Talent & Leadership
Builds a calibrated, reusable benchmark from source material so every later screen, shortlist or review is graded against the same bar.
2–3 days → ~10 minutes
For one complete, review-ready pass
No coding required
— USE CASES
Turn the evidence from your best performers into a benchmark future candidates are screened against.
Give every assessor the same calibrated definition instead of individual interpretations.
Build one Blueprint per client or role family and reuse it across engagements.
— HOW IT BEHAVES
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
The standard for the talent population is calibrated from real evidence before a single person is assessed against it.
The run works from assessment and review evidence you supply, so conclusions about the talent population are anchored to your evidence rather than general model knowledge.
Findings across the talent population are pulled together into a written output ready for review.
A Blueprint is a reusable benchmark — the calibrated definition of what good looks like for a role or standard. Codifying a hiring bar is the typical trigger — turn the evidence from your best performers into a benchmark future candidates are screened against. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means 2–3 days of manual work.
Skillsize turns that work into a Skill: you supply the material, and what comes back is a calibrated, reusable Blueprint, with matching logic ready for screening and benchmarking. 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. Net effect: 2–3 days down to ~10 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Build a Blueprint 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.
Screens candidate evidence against a saved Blueprint, applying the same calibrated bar and traceable reasoning to every applicant.
Maps a set of roles against required competencies and renders the result as a matrix, with clarification and review steps built in.