ai-usage-coach

AI work delegation evaluation assesses prompts, context scoping, tool selection, and verification. This skill analyzes session logs to provide actionable coaching, identifying recurring issues and suggesting targeted improvements for effective human-AI collaboration.

Improving AI prompts and context scoping requires targeted coaching based on session analysis. This skill reviews delegation patterns, identifies where context or skill use falls short, and provides actionable recommendations to enhance prompt engineering and subagent selection.

Python is required for privacy scanning and processing tasks. The skill depends on the privacy_scan.py script to perform secure content analysis, ensuring that AI delegation session logs are reviewed safely before generating coaching reports.

Generating shareable reports is supported through the 'shareable' mode. This mode analyzes AI work delegation practices while applying privacy considerations, allowing you to safely distribute coaching insights and diagnostic results across your team.

Analyzing recurring AI delegation issues across multiple repositories requires a cross-repository review lens. This skill offers repository and cross-repository lenses to evaluate patterns, diagnose recurring struggles, and route improvements effectively across different projects.

The teacher-pack mode supports reusable AI coaching materials by generating structured teaching outputs. This mode analyzes delegation practices and transforms coaching recommendations into materials designed to train and improve future AI collaboration workflows.