video-transcript
Skill448 starsChanged 5 days agoMITView on GitHub
Extract video transcripts: yt-dlp subtitles to clean paragraphs.
17 other projects use a version of this, 1 of them edited.
Adopted by
Most recently taken up by
- spongetimblin/claude-skill-librarytheir own version, first seen Nov 8, 2026
- thatjuan/agent-skillstheir own version, first seen Nov 8, 2026
- Ntmib/jarvis-architecttheir own version, first seen Nov 1, 2026
- guipi888/workbuddy-video-transcripttheir own version, first seen Oct 25, 2026
- juliasadler/muse-skills-cntheir own version, first seen Oct 17, 2026
- PerpperQAQ/video-transcripttheir own version, first seen Oct 13, 2026
Other versions17 projects use a version of this.
Word for word · 0
None found.
Edited · 1
- notque/claude-code-toolkit★ 44897% same
Wrote their own version · 16
- ZeroPointRepo/youtube-skills★ 972same name
- Backtthefuture/huangshu★ 274same name
- artemchuikin/youtube-skills★ 273same name
- bozhouDev/video-skills-toolkit★ 147same name
- Ntmib/jarvis-architect★ 4same name
- shalomb/agent-skills★ 3same name
- kuiilabs/claude-skills★ 2same name
- guipi888/workbuddy-video-transcript★ 1same name
- illli-studio/skills★ 1same name
- juliasadler/muse-skills-cn★ 1same name
6 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository64 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- assessmentSkill
- dataSkill
- business-opsSkill
- code-qualitySkill
- comment-qualitySkill
- condenseSkill
- joy-checkSkill
- content-engineSkill
- contentSkill
- headlinesSkill
- image-genSkill
- image-to-videoSkill
- series-plannerSkill
- topic-brainstormerSkill
- video-editingSkill
- writingSkill
- domainSkill
- cli-designSkill
- frontendSkill
- frontend-slidesSkill
- jev-designSkill
- webgl-card-effectsSkill
- game-asset-generatorSkill
- game-devSkill
- game-trailerSkill
- motion-pipelineSkill
- browser-jev-automationSkill
- cve-source-checkSkill
- deploySkill
- endpoint-validatorSkill
- headless-cron-creatorSkill
- kubernetesSkill
- githubSkill
- accountsSkill
- auto-dreamSkill
- building-with-jevSkill
- codexSkill
- docs-sync-checkerSkill
- doSkill
- dSkill
- grill-jevSkill
- toolkitSkill
- workflow-helpSkill
- debuggingSkill
- plant-seedSkill
- processSkill
- pr-workflowSkill
- quickSkill
- testingSkill
- with-anti-rationalizationSkill
- workflowSkill
- worktree-agentSkill
- programmingSkill
- architecture-deepeningSkill
- codebase-analyzerSkill
- markdown-converterSkill
- news-collectionSkill
- researchSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 10 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 51
Default output is plain paragraph text with [Music]-style cues stripped and the rolling duplicates of auto-captions deduplicated.
“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Video Transcript
Pull a video's transcript as readable paragraphs. Two paths, in order:
Path 1 — uploader subtitles (accurate, prefer when present):
yt-dlp --skip-download --write-subs --sub-langs en --sub-format vtt \
-o '<work-dir>/%(id)s' '<URL>'Path 2 — auto-generated captions (fallback when path 1 writes no file):
yt-dlp --skip-download --write-auto-subs --sub-langs en --sub-format vtt \
-o '<work-dir>/%(id)s' '<URL>'Then clean the VTT into paragraphs:
python3 skills/research/video-transcript/scripts/vtt_to_paragraph.py <work-dir>/<id>.en.vttDefault output is plain paragraph text with [Music]-style cues stripped and the rolling duplicates of auto-captions deduplicated. Use --timestamps for [mm:ss] markers, --keep-brackets to keep cue tags, -o FILE to write to a file.
For other languages, change --sub-langs (e.g. de, en.*). List what a video offers with yt-dlp --list-subs '<URL>'.
Error handling
Both paths write no .vtt file
Cause: video has no subtitles or captions in the requested language.
Solution: run yt-dlp --list-subs '<URL>' and pick an available language; if none exist, report that and offer audio transcription via the markdown-converter skill on a downloaded audio file.
HTTP 429 / "Sign in to confirm"
Cause: platform rate-limiting the host.
Solution: wait and retry with --sleep-requests 2; keep request volume low.
Cleaner output repeats lines
Cause: VTT came from a third path (e.g. translated captions) with cue formats the dedupe misses.
Solution: rerun the cleaner; if repeats remain, file the sample VTT alongside a fix to vtt_to_paragraph.py.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

