Calibrated talent decisions
Assess every role against the same defined bar, so the outcome does not depend on who ran the review.
— Talent & Leadership
Internal Mobility Matchmaker
Reads a CV, Hogan report and performance notes to establish growth appetite and development needs, takes an internal role list (pasted, uploaded or researched) and ranks the available internal moves with a development rationale explaining why each one stretches the right capability.
- Talent & Leadership
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~25 minutes
For a typical multi-document review workflow
No coding required
- Input
- Assessment, review or performance evidence you already hold
- Output
- A calibrated view of each role with the rationale shown
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 weeks per run
— USE CASES
What people use Internal Mobility Matchmaker for
Evidence a committee can question
Every rating traces back to the evidence behind it, so a board or committee can interrogate it.
Consistent development at scale
Produce the same depth of output for the whole population, not only the most visible names.
What it works from
- Assessment, review or performance evidence you already hold
- Your competency model, success profile or leadership standard
What you get back
- A calibrated view of each role with the rationale shown
- A population-level read a talent committee can act on
— HOW IT BEHAVES
How Internal Mobility Matchmaker produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Whole sets of org data, role documentation and headcount exports at once
All of your org data, role documentation and headcount exports is processed as one set, so patterns across documents surface instead of being read one file at a time.
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.
Composed as work product
Findings on the organisation in scope are written up as a document that reads like professional output, with each claim tied back to a role.
Why this is expensive by hand
Judgements about the organisation in scope are usually made from evidence spread across assessments, reviews and conversations, with the bar shifting between assessors. In practice it shows up as calibrated talent decisions: assess every role against the same defined bar, so the outcome does not depend on who ran the review. The value sits in the rigour, not the typing — yet the rigour is exactly what gets traded away when there is only 1–2 weeks of capacity for it.
How this Skill produces it
As a Skill, the work is already sequenced. You bring the evidence, and the run produces a calibrated view of each role with the rationale shown plus a population-level read a talent committee can act on. 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, 1–2 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
- 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
Internal Mobility Matchmaker 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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