Manage and retrieve project learnings with review, search, pruning, and export.
npx skills add https://github.com/mostafasudo/warpy --skill learn-mostafasudo
Please help me install this Agent Skill. Skill: learn Source: https://github.com/mostafasudo/warpy/tree/main/.codex/skills/gstack/learn Command: npx skills add https://github.com/mostafasudo/warpy --skill learn-mostafasudo
This Skill streamlines the process of managing project learnings, allowing you to review, search, prune, and export knowledge across sessions. It's ideal for situations where you need to recall past learnings, identify patterns, or proactively suggest past solutions.
To review learnings from your project, run the 'learn' command.
High-intent search queries and answers about installing and using this skill.
Project learning management involves storing, reviewing, and searching past learnings across sessions to drive continuous improvement. It is needed to recall historical insights, identify patterns, and proactively suggest past solutions to avoid repeating mistakes.
To review and search project learnings from previous sessions, run the 'learn' command. This retrieves stored knowledge from your project learning databases and session files, allowing you to quickly summarize key insights and lessons.
Yes, you can export project learnings for reporting and documentation purposes. The data export feature allows you to extract retrieved knowledge and insights from your session files for external use.
Yes, you need access to project learning databases and session files to manage and prune project learnings. These repositories store the historical knowledge required for the review, search, and proactive suggestion features.
The best way to organize team collaboration insights is by using a knowledge management system that supports pruning and search. This ensures relevant learnings are retained across sessions and proactively suggested when similar project contexts arise.
You should prune project learnings during continuous improvement initiatives when outdated knowledge no longer applies. Pruning removes obsolete entries from your project learning databases, ensuring search results and proactive suggestions remain accurate.
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