AI-Assisted Performance Review Skill

The uncomfortable review question of the decade: when a report ships twice the output with AI, what did they do? Volume stopped measuring effort; polish stopped measuring skill. Punishing AI use is as wrong as crediting the model's work to the human. This skill separates the signals — and gives managers the conversation, not just the theory.

What This Skill Produces

• A what-measures-whom analysis of the role's current evaluation criteria
• Rewritten criteria that measure the human: judgment, verification, outcomes, leverage
• Calibration rules for teams with uneven AI adoption
• Conversation scripts for the three hard cases

Required Inputs

Ask for (if not already provided):

• The role and current review criteria (the rubric, or how it really works)
• How AI shows up in the work — which tasks, how much of the output it drafts, what the tooling reality is
• The specific situation, if any: one person's review? team calibration? criteria rewrite?
• The org's AI stance — encouraged? tolerated? policy exists? (Reviews must not punish sanctioned behaviour)