error-record

Log AI-generated errors and resolutions into dated Markdown files.

Updated Feb 17, 2026
One-click install
npx skills add https://github.com/Gatsbyhateyou/gatsby-website --skill error-record
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: error-record
Source: https://github.com/Gatsbyhateyou/gatsby-website/tree/main/.cursor/skills/error-record
Command: npx skills add https://github.com/Gatsbyhateyou/gatsby-website --skill error-record

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you and the AI learn from mistakes by systematically recording and summarizing errors made during AI-assisted tasks, preventing recurrence.

Core Features & Use Cases

  • Error Summarization: Captures the context, cause, and resolution of AI errors.
  • Chronological Archiving: Organizes error records by date in a dedicated project folder.
  • Preventative Learning: Creates a knowledge base to avoid repeating past mistakes.
  • Use Case: After an AI incorrectly formats a code snippet, use this Skill to log the error, its cause (e.g., misunderstanding of specific syntax), the fix, and a lesson learned for future code generation.

Quick Start

Record the recent error and its correction in the error-record folder.

Frequently Asked Questions about error-record

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

FAQPage Schema
How do I log AI-generated code errors for future reference?

To log AI-generated code errors, this Skill records the scenario, manifestation, cause, correction, and lessons learned into a dated Markdown file. It archives these records chronologically within a dedicated 'error-record' directory in your project.

What is the best way to document AI mistakes and prevent recurrence?

The best way to document AI mistakes is by systematically summarizing the context, root cause, and resolution of each error. This builds a preventative knowledge base that helps the AI learn from past errors and avoid repeating them.

How does archiving AI debugging errors into a knowledge base work?

Archiving AI debugging errors works by capturing the error context and its fix, then saving them as structured Markdown files. This creates a historical knowledge base within your project to track continuous improvement and corrective actions.

Can I use this error logging technique for any AI-assisted coding project?

Yes, you can use this error logging technique for any AI-assisted coding project. It requires no specific dependencies and simply creates an 'error-record' directory to store dated Markdown files for your code quality tracking.

What specific fields are needed to record AI mistakes systematically?

To record AI mistakes systematically, you need specific fields for the scenario, manifestation, cause, correction, and lessons learned. This structure ensures all error records capture the full context and preventative measures.