ReddRadar
Agent skill
youtube-to-markdown
Use when user asks YouTube video extraction, get, fetch, transcripts, subtitles, or captions. Writes video details and transcription into structured markdown file.
Stars
7
Forks
1
Install this agent skill to your Project
npx add-skill https://github.com/vre/flow-state/tree/main/docs/youtube-to-markdown/research/2026.01.14 token usage test/code/lite
SKILL.md
YouTube to Markdown (Lite Variant)
Optimized variant: No polish steps (4, 7, 8) + combined workflows (5+6, 10a+10b). Result: 2 subagents for minimum cost.
Execute all steps sequentially without asking for user approval.
Step 0: Check extracted before
bash
python3 ./check_existing.py "<YOUTUBE_URL>" "<output_directory>"
If returns exists: true: Skip to Step 10 (comments).
Step 1: Extract data
bash
python3 extract_data.py "<YOUTUBE_URL>" "<output_directory>"
Step 2: Extract transcript
If video language is en, proceed directly. If non-English, ask user which language.
bash
python3 extract_transcript.py "<YOUTUBE_URL>" "<output_directory>" "<LANG_CODE>"
Fallback (only if transcript unavailable)
bash
python3 extract_transcript_whisper.py "<YOUTUBE_URL>" "<output_directory>"
Step 3: Deduplicate transcript
bash
python3 ./deduplicate_vtt.py "<output_directory>/${BASE_NAME}_transcript.vtt" "<output_directory>/${BASE_NAME}_transcript_dedup.md" "<output_directory>/${BASE_NAME}_transcript_no_timestamps.txt"
Copy dedup as final transcript (no polish steps):
bash
cp "<output_directory>/${BASE_NAME}_transcript_dedup.md" "<output_directory>/${BASE_NAME}_transcript.md"
Step 5: Summarize transcript (combined summarize + tighten)
task_tool:
- subagent_type: "general-purpose"
- model: "sonnet"
- prompt:
INPUT: <output_directory>/${BASE_NAME}_transcript_no_timestamps.txt
OUTPUT: <output_directory>/${BASE_NAME}_summary_tight.md
FORMATS: ./summary_formats.md
1. Classify content type:
- TIPS: gear reviews, rankings, practical advice
- INTERVIEW: podcasts, conversations, Q&A
- EDUCATIONAL: concept explanations, analysis
- TUTORIAL: step-by-step instructions
2. Read FORMATS and create summary using format for detected type.
3. Self-review: Cut fluff, enforce <10% of transcript bytes, prefer lists over prose.
4. Save final tightened summary to OUTPUT.
Rules:
- Skip ads, sponsors, self-promotion
- Preserve original language
ACTION REQUIRED: Use Write tool NOW to save to OUTPUT file.
Step 10: Extract and analyze comments (combined)
bash
python3 ./extract_comments.py "<YOUTUBE_URL>" "<output_directory>"
python3 ./prefilter_comments.py "<output_directory>/${BASE_NAME}_comments.md" "<output_directory>/${BASE_NAME}_comments_prefiltered.md"
task_tool:
- subagent_type: "general-purpose"
- model: "sonnet"
- prompt:
SUMMARY: <output_directory>/${BASE_NAME}_summary_tight.md
COMMENTS: <output_directory>/${BASE_NAME}_comments_prefiltered.md
Read SUMMARY to understand video content and type.
Extract insights from COMMENTS that ADD VALUE beyond summary:
- Corrections/Extensions
- Alternative applications
- Debates/controversies
Format as:
## Comment Insights
**Key Takeaway**: [one sentence]
[Categories based on video type with @username attributions]
Rules:
- Only insights NOT already in summary
- Be ruthlessly concise
ACTION REQUIRED: Read SUMMARY, append Comment Insights section, and write back using Write tool.
Step 9: Create output files
bash
python3 finalize.py "${BASE_NAME}" "<output_directory>"
Outputs:
youtube - {title} ({video_id}).md- Main summary with comment insightsyoutube - {title} - transcript ({video_id}).md- Description and transcript
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