reflect

Analyze conversation feedback to propose patch-level updates to existing SKILL.md files.

1|Updated Apr 14, 2026
One-click install
npx skills add https://github.com/materkey/cc-plugins --skill reflect-materkey
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/materkey/cc-plugins/tree/main/plugins/reflect/skills/reflect
Command: npx skills add https://github.com/materkey/cc-plugins --skill reflect-materkey

SYSTEM DOCUMENTATION & REQUIREMENTS

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.

Frequently Asked Questions about reflect

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I update skill instructions based on user corrections from a conversation?

To update skill instructions from user corrections, analyze the active conversation to detect repeated feedback and skill failures, then map those signals to existing SKILL.md files and apply targeted patch-level edits to improve future behavior.

What is the best way to capture workflow preferences and turn them into prompt improvements?

Capturing workflow preferences for prompt improvement involves scanning the current session for confirmed patterns and user approvals, filtering the findings to changes that belong inside an existing skill definition, and directly editing the approved instructions.

How does conversation analysis detect skill failures for skill maintenance?

Conversation analysis detects skill failures by reading conversation evidence to identify recurring user corrections, mapping those signals to specific problems in a skill's steps, criteria, or formatting, and separating patch-level issues from architecture-level concerns.

When do I need to escalate a skill failure to an architecture-level workflow instead of a patch?

You need to escalate a skill failure to an architecture-level workflow when the issue is larger than a patch, requiring a new system component rather than modifying existing steps, criteria, formatting, or behavioral instructions in the current SKILL.md file.

Does conversation signal analysis work for fixing output formatting rules in existing skills?

Yes, conversation signal analysis works for fixing output formatting rules by identifying repeated user corrections regarding formatting within the session and applying those findings as targeted edits to the relevant existing skill definitions.

Can I use conversation reflection to correct tool selection choices in a coding assistant skill?

Yes, you can use conversation reflection to correct tool selection choices by identifying where the user repeatedly corrected the assistant's tool choices, then applying those workflow corrections directly into the existing skill's behavioral instructions.