ai-feature-definition

What problem does it solve?

This Skill helps product teams turn high-level product intent into a complete, actionable AI feature specification that accounts for probabilistic model behavior, failure modes, and operational constraints so engineering and ML teams can implement reliably.

Core Features & Use Cases

• Comprehensive Spec Generation: Produces desired model behaviour, input/output examples, acceptance criteria, and non-functional requirements.
• Risk & Recovery Planning: Defines confidence thresholds, fallback ladders, human-in-the-loop checkpoints, and deterministic fallbacks for low-confidence outputs.
• Monitoring & Feedback Design: Specifies drift detection triggers, feedback collection mechanisms, and retraining/review cadence.
• Use Case: Craft an AI PRD for a customer-support summarizer that includes 5 example input/output pairs, acceptable output ranges, monitoring alerts, and human review rules.

Quick Start

Write a complete AI feature specification for an AI-powered customer support summarizer including inputs, outputs, five example input/output pairs, confidence thresholds, fallback logic, human-in-the-loop requirements, monitoring triggers, and non-functional SLOs.