youtube-transcript-pipeline-lite

Run a lightweight YouTube transcript workflow: transcribe, attribution cleanup, translation, and packaging with minimal tooling. Use for repeatable transcript handoff tasks when you need a concise, auditable process over custom automation.

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Install skill "youtube-transcript-pipeline-lite" with this command: npx skills add bluebirdback/youtube-transcript-pipeline-lite

YouTube Transcript Pipeline (Lite)

Quick Start

Use this when a user asks for:

  • YouTube transcript generation and cleanup
  • speaker correction around interview/interjector vs main speaker
  • translated transcript output while preserving timestamps/speakers
  • ready-to-share folder packaging

Minimal Workflow

  1. Transcribe

    • Run your existing transcript flow for the target video (word-level preferred for reliable speaker calibration).
    • Keep all raw outputs.
  2. Speaker cleanup (small-impact)

    • Preserve the default/primary speaker mapping.
    • Only flip clearly short-interjection/question lines when they are obviously misattributed.
    • Keep line count and timestamps unchanged.
  3. Translate (optional)

    • Translate content line-by-line.
    • Keep format exactly: [HH:MM:SS] Speaker: text.
    • Keep technical terms unless explicitly asked to simplify.
  4. Package for handoff

    • Create concise structure: transcripts/, artifacts/, MANIFEST.txt.
    • Include one reviewed transcript + one translated version when asked.

What not to do in this skill

  • Do not introduce heavy automation assumptions.
  • Do not change line/timestamp structure unless user explicitly asks.
  • Do not aggressively relabel all speaker turns; prefer conservative flips.

Quality checks

  • Validate final line counts against source.
  • Confirm active final files are present and clearly named.
  • Keep every major handoff stage discoverable in manifest.

Reference

See references/limits.md for quick trade-offs and rollback guidance.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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