What problem does it solve?
This Skill helps you capture repeated user corrections, approvals, and preferences from the current conversation and convert them into concrete improvements for an existing Skill. It reduces the chance of repeating the same mistakes across future sessions by updating the Skill instructions directly.
Core Features & Use Cases
- Conversation Signal Analysis: Scans the active session for meaningful user corrections, confirmed patterns, workflow preferences, and clear skill mistakes.
- Patch-Level Skill Remediation: Filters findings to changes that belong inside an existing SKILL.md file, such as revised steps, better criteria, or clearer output format rules.
- Architecture Escalation Detection: Identifies when the issue is larger than a patch and should be routed to a separate architecture-focused workflow instead of modifying the current skill.
- Use Case: After a session where a user repeatedly corrected how a coding assistant formats findings or chooses tools, use this Skill to identify those signals, map them to the relevant existing skill, and apply targeted edits to improve future behavior.
Quick Start
Ask the assistant to run the reflect skill on the current conversation and propose approved edits for any existing skill that the user corrected.