High-volume screening
Screen a large applicant pool against a calibrated bar without the standard drifting.
— Talent & Leadership
Screen against a Blueprint
Screens candidate evidence against a saved Blueprint, applying the same calibrated bar and traceable reasoning to every applicant.
- Talent & Leadership
- Deterministic scoring
- Traceable reasoning
- Runs anywhere
half a day → ~10 minutes
For one complete, review-ready pass
No coding required
- Input
- Candidate CVs or evidence
- Output
- A screening result per candidate against the Blueprint
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~half a day per run
— USE CASES
What people use Screen against a Blueprint for
Multi-recruiter consistency
Give every screener the same Blueprint so shortlists are comparable.
Defensible rejection records
Keep a traceable reason, against explicit criteria, for every screening decision.
What it works from
- Candidate CVs or evidence
- The Blueprint to screen against
- Any pass thresholds
What you get back
- A screening result per candidate against the Blueprint
- Consistent reasoning behind each decision
- An audit trail for the process
— HOW IT BEHAVES
How Screen against a Blueprint produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Every candidate graded against one saved standard
Each candidate is measured against a calibrated standard you own, so the bar for the candidate pool stays identical between runs, assessors and months.
Composed as work product
Findings on the candidate pool are written up as a document that reads like professional output, with each claim tied back to a candidate.
Grounded in your own CVs, applications and interview notes
The run works from CVs, applications and interview notes you supply, so conclusions about the candidate pool are anchored to your evidence rather than general model knowledge.
CVs, applications and interview notes reshaped for use
Content is restructured into the form your deliverable or downstream system expects, with each candidate kept intact.
Why this is expensive by hand
Every talent & leadership team needs screen against a Blueprint — and almost none of them do it the same way twice. High-volume screening is the typical trigger — screen a large applicant pool against a calibrated bar without the standard drifting. Done properly it is defensible; done at pace it becomes a judgement call nobody can retrace. And "properly" usually means half a day of manual work.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; a screening result per candidate against the Blueprint comes out, alongside consistent reasoning behind each decision. 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: half a day down to ~10 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Who it's for
- CHROs and talent management leads
- Succession and leadership development teams
- Executive assessors and coaches
- Consultants running talent reviews
Run it in Skillsize — or export it anywhere
Screen against 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.
ChatGPTClaudeCopilotAI Products (MCP)
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