Youtube Korean Transcript

PIP_DISABLE_PIP_VERSION_CHECK=1 <PYTHON_CMD> -m pip install yt-dlp

3) Run the extractor

Run from this skill directory:

<PYTHON_CMD> scripts/extract_youtube_ko_transcript.py \
  --video "https://www.youtube.com/watch?v=VIDEO_ID" \
  --output-dir artifacts

If YouTube blocks requests, retry with network/auth options:

<PYTHON_CMD> scripts/extract_youtube_ko_transcript.py \
  --video "https://www.youtube.com/watch?v=VIDEO_ID" \
  --output-dir artifacts \
  --cookies /path/to/cookies.txt

or

<PYTHON_CMD> scripts/extract_youtube_ko_transcript.py \
  --video "https://www.youtube.com/watch?v=VIDEO_ID" \
  --output-dir artifacts \
  --proxy-url "http://user:pass@host:port"

If your environment has TLS interception/certificate issues:

<PYTHON_CMD> scripts/extract_youtube_ko_transcript.py \
  --video "https://www.youtube.com/watch?v=VIDEO_ID" \
  --output-dir artifacts \
  --no-check-certificate

4) Confirm generated output

Expect one file:

• <video_id>.ko.readable.md
• If chapters exist on YouTube metadata, readable output is grouped by chapter titles.
• If chapters do not exist, output falls back to fixed section ranges by --section-minutes.

Frontmatter/YAML properties to check:

• title: ...
• url: ...
• video_id: ...
• channel: ...
• published: YYYY-MM-DD
• created: YYYY-MM-DD
• needs_llm_translation: true|false

Summary/template sections to check:

• ## 📎 Summary Source (Compact)
• ## 📌 Executive Summary
• ## 🔍 Detailed Summary
• ## 💡 Key Insights & Action Items
• ## 📝 Transcript

5) Translate + summarize in your LLM workflow

Token-saving execution policy (MUST):

• Use exactly one LLM edit call per video (replace or one-shot file edit). Avoid multi-turn read/replace/write loops.
• Use ## 📎 Summary Source (Compact) as the primary input for summary generation.
• Keep summary length limits:
  • Executive Summary: 4~6 sentences
  • Detailed Summary: 4~6 bullets
  • Key Insights & Action Items: 3~5 bullets
• Remove ## 📎 Summary Source (Compact) before final delivery unless the user explicitly asks to keep it.

Case A: needs_llm_translation: true

• Translate transcript body text into Korean.
• Keep transcript section headers and [HH:MM:SS] timestamps exactly unchanged.
• Keep proper nouns/product names in original form when translation is awkward.
• Fill summary sections in Korean using compact summary source.
• Overwrite the same file (<video_id>.ko.readable.md) in place.
• Update YAML property to needs_llm_translation: false.

Case B: needs_llm_translation: false

• Do not rewrite transcript body.
• Fill or refine summary sections in Korean using compact summary source only.

5-1) Humanizer-KR pass (AI 티 제거)

After step 5, you MUST apply a humanized Korean style pass.

Core rewriting rules:

• Avoid hype-heavy words (핵심적, 획기적, 중대한, 새 지평, 패러다임 전환) unless objectively justified.
• Replace vague authority claims (전문가들은, 업계 관계자에 따르면) with concrete sources, or remove.
• Reduce repetitive connectors (이를 통해, 아울러, 나아가, 이러한 맥락에서).
• Reduce overuse of ~적 adjectives and inflated Sino-Korean wording.
• Avoid verbose forms like ~에 있어서, ~함에 있어; rewrite to direct Korean.
• Prefer concrete facts, numbers, and observable outcomes over abstract praise.
• Keep sentence rhythm mixed (short + medium); avoid monotonous, machine-like cadence.
• Preserve original meaning and factual content; do not alter timestamps or section boundaries.
• Keep professional tone, but avoid press-release style phrasing.

5-2) LLM Post-Translation Prompt Templates

Use one of the templates below in your current environment (Gemini/OpenAI/Claude).

Template A (Korean default):

다음 Markdown 파일을 수정해 주세요.
파일 경로: <READABLE_FILE_PATH>

규칙:
1) 이 작업은 한 번의 편집 호출로 끝냅니다.
2) `## 📎 Summary Source (Compact)`만 사용해 요약을 작성합니다.
3) `needs_llm_translation: true`이면 `## 📝 Transcript` 본문을 자연스러운 한국어로 번역하고, `false`이면 Transcript는 수정하지 않습니다.
4) `## 📝 Transcript` 아래의 소제목과 `[HH:MM:SS]` 타임스탬프는 원문을 그대로 유지합니다.
5) `## 📌 Executive Summary`는 4~6문장, `## 🔍 Detailed Summary`는 4~6개 bullet, `## 💡 Key Insights & Action Items`는 3~5개 bullet로 작성합니다.
6) 고유명사(인명, 제품명, 프로젝트명)는 의미가 어색해지면 원문을 유지합니다.
7) YAML frontmatter는 유지하되 `needs_llm_translation: true`는 `needs_llm_translation: false`로 바꿉니다.
8) 마지막으로 AI 글쓰기 패턴을 제거합니다: 과장어, 모호한 출처, `~적`/`~에 있어서` 남용, 연결어 남발을 줄이고 더 자연스러운 한국어 문장으로 다듬습니다.
9) 최종본 저장 전 `## 📎 Summary Source (Compact)` 섹션은 삭제합니다(사용자가 유지 요청한 경우 제외).
10) 설명 출력 없이 파일만 덮어써서 저장합니다.

Template B (target language variable):

Edit this markdown file in place.
File path: <READABLE_FILE_PATH>
Target language: <TARGET_LANGUAGE>

Requirements:
1) Complete this in one edit call.
2) Use only `Summary Source (Compact)` for summary writing.
3) If `needs_llm_translation: true`, translate transcript body into <TARGET_LANGUAGE>; otherwise, do not edit transcript body.
4) Preserve transcript section headings and `[HH:MM:SS]` timestamps exactly.
5) Keep summary lengths: Executive 4-6 sentences, Detailed 4-6 bullets, Action Items 3-5 bullets.
6) Keep proper nouns in original form when translation hurts clarity.
7) Keep YAML frontmatter unchanged except setting `needs_llm_translation: false` when translation is done.
8) Apply a humanization pass: remove hype-heavy wording, vague attribution, repetitive connectors, and overly formulaic AI phrasing.
9) Remove the `Summary Source (Compact)` section before final delivery unless the user asks to keep it.
10) Save changes to the same file with no extra commentary.

6) Apply response-quality checks

• Verify the file includes both first and last timestamps.
• Verify every timestamp is HH:MM:SS.
• Verify transcript section headers and timestamp tokens were not changed by translation.
• Verify summary sections were written from Summary Source (Compact) content.
• Verify all three summary sections are filled (not placeholders).
• Verify summary length limits are met.
• Verify Summary Source (Compact) is removed in the final file by default.
• Verify wording is not overly promotional or template-like AI prose.
• If any check fails, fix the file and re-run the checks before returning.
• If user asks for polishing, only fix obvious ASR wording issues.

7) Session hygiene for token savings

• Use one fresh chat/session per video URL.
• Do not continue from prior unrelated long threads when running this skill.

Script Options

extract_youtube_ko_transcript.py supports:

• --video: YouTube URL or 11-char video ID (required)
• --output-dir: destination folder (default: artifacts; relative paths map to original project path in Gemini temp sessions, otherwise current working directory)
• --prefer-korean-languages: preferred Korean track codes (default: ko,ko-KR)
• --source-languages: fallback source track order (default: en,en-US,ja,es,fr,de)
• --languages: backward-compatible alias of --source-languages
• --proxy-url: proxy URL for yt-dlp
• --proxy-http-url: legacy alias for HTTP proxy
• --proxy-https-url: legacy alias for HTTPS proxy
• --cookies: Netscape-format cookies file path
• --user-agent: custom User-Agent string
• --no-check-certificate: disable TLS certificate verification (use only when needed)
• --no-chapters: disable chapter-based organization and always use fixed section ranges
• --section-minutes: readable markdown section size (default: 10)
• --summary-compact-sections: max sections included in compact summary source (default: 8)
• --summary-compact-points: max representative points per section in compact summary source (default: 2)
• --summary-compact-chars: max characters per representative point in compact summary source (default: 180)

Failure Handling

• If transcript fetch fails, report the exact error briefly.
• If no subtitle track is accessible, state that clearly and stop.
• If YouTube blocks the network/IP (HTTP 429), retry later, change network, disable Tailscale Exit Node/VPN/cloud egress, or use --cookies/--proxy-url.
• If TLS certificate verification fails, retry with --no-check-certificate only in restricted environments.