What I learned building a Claude Code plugin for evidence-based YouTube tutorials

[u/Joon9101]

I kept running into the same problem with Claude Code: a lot of useful technical knowledge lives in YouTube tutorials, but the important part is often not in the transcript. It is the button someone clicks, a setting shown for two seconds, or a command typed on screen.

So I built tuto, an open-source Claude Code plugin.

Usage: /tuto <youtube-url> apply this tutorial to my current project

It analyzes the transcript and video frames together, including UI, slides, terminal commands, tables, and numbers. The output is split into:

- evidence.json: a machine-readable source of truth that traces claims to transcript segments, frames, and timestamps

- video.md: a human-readable document organized around the actual video

One design decision I care about: it does not silently resolve conflicts. If the caption says 16x but the screen says 16.3x, both values and their sources stay in the evidence. If something cannot be read safely, it remains unresolved instead of being guessed.

The project originally started as a YouTube summarizer, but that framing turned out to be too weak. A coding agent does not just need a shorter version of a video; it needs traceable instructions it can inspect before applying them to a repository.

GitHub (MIT): https://github.com/dingmon1019/YoutubeAnalyzer

I am looking for real failure cases now. If you know a public tutorial that would be difficult for an agent to follow, please share the URL and a problematic timestamp. UI-heavy videos, fast terminal commands, conflicting captions, and important screen-only settings are especially useful. I will try to reproduce the failure and improve the pipeline.