youtube-research-kit

YouTube Research Kit

Extract structured data from YouTube videos, channels, and playlists for content research. Powered by yt-dlp — no API key required.

Version: 1.2.0 Prerequisite: yt-dlp >= 2024.01.01, jq (optional, for JSON formatting)

When user provides a YouTube URL or asks about YouTube content research, use this skill.

Prerequisites

# macOS
brew install yt-dlp
pip
pip install yt-dlp
Verify
yt-dlp --version

Operations

1. Video Metadata

Extract title, channel, stats, description, tags, and available formats.

yt-dlp --dump-json --no-playlist --skip-download "URL"

Parse key fields from JSON output:

| Field | JSON path | |-------|-----------| | Title | .title | | Channel | .channel / .uploader | | Channel URL | .channel_url | | Upload date | .upload_date (YYYYMMDD → reformat to YYYY-MM-DD) | | Duration | .duration (seconds → convert to H:MM:SS) | | Views | .view_count | | Likes | .like_count | | Comment count | .comment_count | | Description | .description | | Tags | .tags[] | | Categories | .categories[] | | Thumbnail | .thumbnail | | Available heights | .formats[].height (deduplicate, filter where .vcodec != "none") |

Output format: Present as a Markdown table with key stats, followed by description and tags sections.

2. Transcript / Subtitles

List available languages:

yt-dlp --list-subs --no-playlist --skip-download "URL"

Download subtitles as SRT:

yt-dlp --skip-download --no-playlist \
  --write-sub --write-auto-sub \
  --sub-lang en \
  --sub-format vtt --convert-subs srt \
  -o "/tmp/yt-sub-%(id)s.%(ext)s" "URL"

After download, read the .srt file and clean it: 1. Remove sequence numbers (lines matching ^\d+$) 2. Extract timestamps from timing lines (^\d{2}:\d{2}:\d{2}) 3. Strip HTML tags (<[^>]+>) 4. Deduplicate consecutive identical lines

Output format: [HH:MM:SS] subtitle text — one line per caption segment.

Replace en with user's requested language code. Common codes: en, zh-Hans, zh-Hant, ja, ko, es, fr, de, pt, ru.

3. Comments

yt-dlp --dump-json --no-playlist --skip-download \
  --write-comments \
  --extractor-args "youtube:max_comments=20,all,100,0" "URL"

Parse comments from JSON: .comments[] array, each with:

| Field | JSON path | |-------|-----------| | Author | .author | | Text | .text | | Likes | .like_count | | Pinned | .is_pinned | | Hearted | .is_favorited |

Sort by .like_count descending. Adjust max_comments=N for custom count.

Output format: Numbered list with author, like count, and quoted text.

4. Playlist Analysis

yt-dlp --flat-playlist --dump-json "PLAYLIST_URL"

Output is one JSON object per line. Parse each for:

Output format: Table with columns: #, Title, Duration, Views.

5. Channel Overview

yt-dlp --flat-playlist --dump-json --playlist-end 20 "CHANNEL_URL/videos"

Append /videos to channel URL if not present. Parse same fields as playlist.

Output format: Table with columns: #, Title, Duration, Views, Date.

Number Formatting

Workflow Guide

When user provides a YouTube URL:

1. Determine URL type (video, playlist, channel, or shorts) 2. Infer what they want or ask if ambiguous 3. Run the appropriate yt-dlp command 4. Parse JSON and present formatted Markdown 5. Offer follow-ups: "Want me to summarize this transcript?" / "Need the comments too?"

When user asks to analyze a video:

1. Extract metadata + transcript in sequence 2. Summarize key points from transcript 3. Present metadata overview + content summary

When user asks to download a video:

Error Handling

About

YouTube Research Kit is an open-source project by SnapVee.

# macOS
brew install yt-dlp
pip
pip install yt-dlp
Verify
yt-dlp --version