Project Root Cause & Health Analyst
Performs forensic analysis on AI-assisted coding sessions to diagnose root causes of rework, scope creep, and codebase friction.
This skill provides a sophisticated diagnostic framework for reviewing AI-driven development sessions, moving beyond simple summaries to explain the underlying 'why' behind project outcomes. By examining iteration signals, scope deltas, and file hotspots, it identifies whether friction stems from vague prompts, repository fragility, or agent-introduced errors. It is an essential tool for developers and leads who want to optimize their AI-assisted workflows, improve prompt engineering standards, and pinpoint brittle areas in their codebase that hinder automated development.
主要功能
01Automated session severity scoring (0–100) to prioritize workflow interventions
021 GitHub stars
03Detailed executive reports featuring metrics on success rates and scope growth
04Friction hotspot mapping to identify specific files or subsystems causing struggle
05Forensic root cause classification (Spec ambiguity, Repo fragility, Agent error)
06Prompt sufficiency evaluation with objective scoring on clarity and boundedness
使用场景
01Auditing complex development sessions to understand why multiple replans were required
02Identifying technical debt by tracking which folders consistently cause AI logic errors
03Optimizing team-wide AI productivity by analyzing the correlation between prompt quality and task success