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Feature Prioritizer (RICE)
Apply RICE scoring that surfaces honest numbers instead of advocacy — with calibrated estimates and the reasoning made explicit.
$8.99
· or 45 creditsSecure checkout via Stripe
About this skill
RICE fails in practice for one reason: the numbers are advocacy. Reach is inflated because the team is excited, effort is underestimated because no one wants to kill their feature, and confidence is whatever makes the score win. This skill applies RICE in a way that surfaces the biases: it asks for the reasoning behind each estimate rather than just the number, flags when estimates are inconsistent with historical data, separates the team's confidence from the model's implied confidence, and produces a prioritized stack with the key assumptions that would flip each ranking. It also generates the questions to ask in the prioritization meeting — the ones that make advocacy visible before it's baked into the roadmap. Bring your feature list and context; get back a scored stack you can defend and the list of assumptions worth stress-testing.
Details
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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