What problem does it solve?
This Skill automates the process of analyzing AI coding session transcripts to identify and codify recurring patterns, preferences, and corrections, thereby improving future AI interactions and project documentation.
Core Features & Use Cases
- Pattern Identification: Detects user corrections, coding style preferences, tool choices, communication styles, and architectural patterns within session logs.
- Scope Categorization: Differentiates between global (applicable to all projects) and project-specific insights.
- Duplicate Checking: Compares extracted insights against existing
CLAUDE.md files to avoid redundancy.
- Use Case: After a series of coding sessions, use this skill to automatically generate entries for your
CLAUDE.md file that capture your preferred way of organizing imports or handling errors, ensuring consistency across projects.
Quick Start
Use the insights skill to analyze the most recent session transcript and present findings.