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reflect

Analyze conversation history to propose prioritized changes to skill files.

Updated Feb 17, 2026
Search Tags:#ai development#learning#conversation analysis#reflection#skill improvement#iterative refinement
One-click install
npx skills add https://github.com/javierhbr/random-poc --skill reflect-javierhbr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reflect
Source: https://github.com/javierhbr/random-poc/tree/main/custom-skills/reflect
Command: npx skills add https://github.com/javierhbr/random-poc --skill reflect-javierhbr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps refine AI capabilities by analyzing past interactions, identifying what worked and what didn't, and suggesting concrete improvements to existing skills.

Core Features & Use Cases

  • Conversation Analysis: Scans chat history for corrections, successes, edge cases, and preferences.
  • Actionable Feedback: Proposes specific, prioritized changes to skill files (constraints, preferences, new coverage).
  • Continuous Improvement: Facilitates an iterative process for enhancing AI skill quality and reliability.
  • Use Case: After a complex coding session where the AI made several mistakes, you can run /reflect coding-assistant to get a summary of errors and suggestions on how to update the coding-assistant skill to avoid those mistakes in the future.

Quick Start

Use the reflect skill to analyze the current session and suggest improvements for the 'data-analysis' skill.

Frequently Asked Questions about reflect

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

FAQPage Schema
How do I analyze conversation history to improve AI skills?▼

Analyzing conversation history to improve AI skills involves scanning past interactions for corrections and successes, then proposing actionable changes to skill files. This process identifies edge cases and preferences for iterative refinement.

What is the best way to refine AI capabilities after a failed coding session?▼

Refining AI capabilities after a failed coding session requires analyzing chat history to pinpoint errors. The system suggests specific updates to skill files, prioritizing high-confidence corrections as constraints to prevent repeating mistakes.

How does conversation analysis identify edge cases for skill improvement?▼

Conversation analysis identifies edge cases for skill improvement by scanning chat history for unexpected scenarios and medium-confidence outcomes. It proposes actionable updates to skill files, expanding coverage to handle these edge cases reliably.

Do I need git access to apply changes from session analysis?▼

Yes, you need git access and access to skill files to apply changes from session analysis. The tool requires these dependencies to propose and implement actionable refinements directly into your existing skill files.

Can I use conversation analysis to extract user preferences for AI development?▼

Yes, you can use conversation analysis to extract user preferences for AI development. It scans chat history to detect medium-confidence preferences and suggests updates to skill files to align future interactions with those expectations.

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