Explain every programming decision with structured expert teaching cards.
npx skills add https://github.com/1786329860/deep-teach --skill deep-teach
Please help me install this Agent Skill. Skill: deep-teach Source: https://github.com/1786329860/deep-teach/tree/main Command: npx skills add https://github.com/1786329860/deep-teach --skill deep-teach
deep-teach prevents AI from only delivering code and instead makes it explain the reasoning behind every programming decision, helping users actually learn while they build.
Tell the assistant to complete your programming task with deep-teach enabled so it produces an expert Teaching Card after the work is done.
High-intent search queries and answers about installing and using this skill.
To get AI to explain programming decisions, you need a teaching workflow that produces structured expert-level cards detailing technology identification, rationale, and alternative comparisons after each coding operation.
An expert-level teaching card for architecture decisions is a structured output that breaks down technology choices, deep-level principles, quantitative advantages, and knowledge transfer guidance to help users learn while building.
You learn the rationale behind dependency installation and function writing by enabling an adaptive teaching mode that generates explanations of source-level principles and trade-offs immediately after the programming operations are completed.
Yes, you can use adaptive output formats for configuration edits and database design tasks, switching between Mini cards for simple changes and Enhanced cards for major architecture decisions to match the complexity.
Yes, deep-teach works with debugging and third-party integrations by applying an always-on teaching mode that explains the reasoning, alternative comparisons, and follow-up learning paths after these specific programming operations.
The best way to understand framework middleware flow and trade-offs is to request an implementation with an expert breakdown that analyzes the architecture selection, middleware flow, and quantitative advantages.
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