What it does
Prepare a Talent Review is a free AI skill for HR business partners and people managers. Give it manager notes and proposed placements, for example on a 9-box grid. It builds a talent review pack with dated evidence per person, calibration prompts and critical-role cover.
It never places anyone. It works in Claude, ChatGPT, Microsoft Copilot and other AI Assistants.
The scope and purpose of the review (for example, a team that feeds succession for one role)
For each person: role, the manager's proposed placement or rating, and the evidence behind it, with source and date
The framework you use, such as 9-box axes and box labels, or a rating scale
Optional: employees' own aspirations, goals, critical roles and risks, existing development plans
A meeting agenda
One page per person: evidence, the proposed placement as supplied, evidence for and against it, their aspirations and development options
Calibration prompts where the notes show a risk
A critical-role continuity view that flags roles with no named cover
An empty action log
How it helps
It works like a talent review template filled in from your manager notes, for a 9-box grid or a rating scale.
Evidence before opinion
Evidence is listed as specific examples with source and date, separate from opinion. Anything unsourced or out of period is marked Unverified. The "evidence recorded" label describes the evidence, never the person.
Prompts for common rating risks
It flags leniency or severity, recency, halo, potential without evidence, and praise for style over outcomes. If "potential" isn't defined, the agenda starts by agreeing it.
The manager's placement, not the AI's
Placements are recorded as given. It never assigns or recommends a placement, rating, promotion or successor, and is instructed not to invent a counterpoint.
Why we think it's useful
Fictional company, role, candidate and people.
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Which AI do you use?
Closing the predictive-validity loop requires structured pre-hire data on every requisition. Assessment scores. Behavioral profiles. Hard-skills signals including AI fluency. Without that dataset, you cannot correlate pre-hire signals with post-hire QoH. You cannot tune the next cohort sharper than the last. The hiring system stays static. The score drifts.
Bryq builds the pre-hire dataset that makes the loop possible.
Claude
ChatGPT
Microsoft Copilot
Something else (Gemini, Mistral and others)
Better with Bryq
Already use Bryq? Add your assessment results.
Link your Bryq account to your AI assistant, and five skills can include your candidates' Bryq results. For example, your debrief shows them next to the interview notes, and your follow-up questions focus on where the two differ. The link only reads data; it never changes anything in Bryq. Results you bring into a chat are shared with your AI provider, like anything else you paste in. Every skill works fully without it.
FAQ
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