Manages complex AI workflows through persistent markdown-based planning and structured progress tracking.
AI Maestro Planning provides a robust framework for managing complex, multi-step tasks by maintaining state across sessions using a three-file markdown system. By enforcing structured logging of goals, research findings, and session progress, it prevents goal drift and helps the AI agent recover from errors through established protocols like the 3-strike rule. This skill is essential for research-heavy projects or deep feature implementations that require more than five tool calls to ensure focus and architectural consistency.
주요 기능
01Five-question reboot system to regain context after interruptions
0224,164 GitHub stars
03Three-file markdown system for goals, findings, and session logs
04Three-strike error recovery protocol for systematic troubleshooting
05Six-rule framework for maintainable AI task execution
06Persistent decision and error tracking for historical reference
사용 사례
01Managing long-running debugging tasks that involve multiple failed attempts and strategy shifts
02Executing complex research projects that require deep-dive analysis across multiple sources
03Implementing large-scale software features with high architectural complexity
