baoyu-youtube-transcript

Overview of baoyu-youtube-transcript skill

What baoyu-youtube-transcript does well

baoyu-youtube-transcript is a YouTube transcript extraction skill for people who need usable text files, not just captions on screen. It downloads transcripts, subtitles, and cover images from a YouTube URL or video ID, supports language selection and translation, and can reformat cached data into markdown or SRT without fetching again. Its biggest practical advantage is reliability: it uses YouTube’s InnerTube API first and falls back to yt-dlp when direct access is blocked.

Best-fit users and real job-to-be-done

This skill is best for researchers, note-takers, archivists, content repurposers, and agents doing Format Conversion from video into markdown, subtitle, or transcript assets. The real job is usually: “take this video, get the transcript in the language I need, keep timestamps or chapters if useful, and save it in a file structure I can reuse later.”

Key differentiators before you install

Compared with a generic “summarize this YouTube video” prompt, baoyu-youtube-transcript gives file-based outputs, caching, language-aware track selection, and a more deterministic extraction path. The repo also includes a speaker-processing prompt in prompts/speaker-transcript.md, which matters if your end goal is a cleaner editorial transcript rather than raw caption lines.

How to Use baoyu-youtube-transcript skill

Install context and runtime requirements

For baoyu-youtube-transcript install, you need either bun or npx available. The skill’s scripts are in skills/baoyu-youtube-transcript/scripts/, and SKILL.md explicitly resolves runtime as bun first, then npx -y bun. If you are evaluating before adoption, read these files first:

• SKILL.md
• scripts/main.ts
• scripts/youtube.ts
• prompts/speaker-transcript.md
• scripts/main.test.ts

That path tells you the actual CLI behavior, fallback logic, and post-processing workflow faster than browsing the whole repo.

How baoyu-youtube-transcript usage works in practice

In normal baoyu-youtube-transcript usage, you call the main script with a YouTube URL or 11-character video ID. The script can:

• fetch transcript tracks
• prefer better subtitle formats such as json3
• choose manual vs auto-generated captions
• translate when available
• output markdown or SRT
• cache metadata and transcript payloads under an output directory

The input quality that matters most is not a long prompt; it is precise extraction intent. Good requests specify:

• video URL or ID
• preferred languages in order
• whether generated captions are acceptable
• desired output format: markdown or SRT
• whether timestamps, chapters, or speakers are needed

A stronger request looks like: “Use baoyu-youtube-transcript on this YouTube URL, prefer en then zh-Hans, allow generated captions, output markdown with timestamps, and save under a reusable output directory.”

Prompting and workflow that reduce guesswork

If you are invoking this through an AI agent, turn a vague goal into an execution-ready instruction. For example:

1. Extraction: “Fetch the transcript for this video ID in en; if unavailable, use translated en from another track.”
2. Formatting: “Return markdown with timestamps for review.”
3. Enhancement: “Then use prompts/speaker-transcript.md to convert the raw transcript into a chaptered, speaker-labeled transcript without translating.”

This two-step workflow matters because speaker labeling is a separate processing task, not the same as raw caption download. The prompt file stresses verbatim fidelity and consistent speaker names, which is useful for interviews, podcasts, and lecture transcripts.

Output structure, caching, and practical tips

The baoyu-youtube-transcript skill stores metadata and transcript cache so repeated reformatting is faster. That is valuable when you want both raw and polished outputs from the same video. Practical tips:

• Use a stable outputDir if you revisit videos often.
• Keep raw transcript output before applying speaker cleanup.
• Use SRT when timing precision matters; use markdown when readability matters.
• If chapter extraction matters, check whether the video description contains timestamp chapters, because the scripts parse chapters from description plus duration.

baoyu-youtube-transcript skill FAQ

Is baoyu-youtube-transcript better than a normal prompt?

Yes, when you need reproducible extraction instead of best-effort reasoning. A normal prompt cannot reliably download subtitle tracks, inspect available languages, cache raw assets, or fall back to yt-dlp. baoyu-youtube-transcript is stronger when your task is acquisition and conversion, not just summarization.

When is this skill a poor fit?

It is a poor fit if there is no accessible transcript track and you expect full speech-to-text transcription from audio alone. This repo is built around YouTube transcript/subtitle retrieval, not a standalone ASR pipeline. It is also overkill if you only want a quick human summary and do not need saved files.

Is baoyu-youtube-transcript beginner-friendly?

Moderately. The skill is script-driven rather than click-driven, so basic comfort with bun, npx, paths, and output folders helps. The good news is the repo is implementation-heavy: scripts/main.test.ts shows selection logic, and SKILL.md gives the command patterns you need to start safely.

How to Improve baoyu-youtube-transcript skill

Give better inputs for better outputs

The fastest way to improve baoyu-youtube-transcript results is to be explicit about transcript selection. Mention language priority, whether manual captions should be preferred, and whether auto-generated captions are acceptable. If you skip this, you may get a usable but lower-quality track or an unexpected translated variant.

Handle common failure modes early

Common issues are invalid video identifiers, blocked direct fetches, missing target-language captions, and confusion between “translate subtitles” versus “summarize transcript.” If extraction fails, inspect scripts/youtube.ts behavior conceptually: the skill already has a fallback path, so your next move is usually changing language constraints or allowing generated captions, not rewriting the whole prompt.

Iterate after the first transcript

For baoyu-youtube-transcript for Format Conversion, the best workflow is iterative:

1. fetch raw transcript
2. verify language and completeness
3. re-run in a different format if needed
4. apply speaker/chapter post-processing

If the first markdown looks messy, do not discard the skill. Instead, keep the cached raw files and rerun formatting or apply prompts/speaker-transcript.md for a cleaner final document. That is where this skill becomes more valuable than a one-off download script.