Yt Research

yt-research — YouTube niche & competitor radar

Find what's taking off on YouTube in your niche, scan competitor channels, rank by virality, and pull transcripts for analysis. Pairs well with an Instagram radar (e.g. reel-radar) and an X radar — this is the YouTube leg.

Search and stats work without any API key via yt-dlp. A YouTube Data API key is an optional, cleaner search path. Transcripts go through TranscriptAPI (see §3).

When to use

• "What's taking off on YouTube about ?"
• "Scan these competitor channels — what's working for them?"
• "Get the transcript / what's in this video ?"
• Gathering proven content ideas before planning a video.

1. Niche search + ranking (default, no key)

python3 scripts/yt_search.py "<query>" --limit 15            # top by views
python3 scripts/yt_search.py "AI agents for business" --by velocity --enrich   # what's accelerating
python3 scripts/yt_search.py "Claude Code" --limit 20 --json # raw JSON for downstream

• --by views (default) — top by absolute views.
• --by velocity — by view-velocity (views / days since upload). The best "rising right now" signal: a fresh video with high daily velocity matters more than an old one with big-but-slow totals. Velocity needs the upload date, so it auto-enables --enrich (an extra per-video lookup, slower).
• --enrich — adds upload date, likes, comments, channel subscribers per video.

2. Scan competitor channels

python3 scripts/yt_search.py --handles "channelA,channelB" --limit 10 --by velocity --enrich

Pulls the latest N videos from each channel (youtube.com/@handle/videos) and ranks them — so you see which formats are firing for a competitor right now. Handle with or without @.

Channel base — references/watchlist.json

Keep a persistent base of tracked channels in references/watchlist.json (ships as a template — fill it with your own niche). Each entry: handle, name, url, channel_id, subs, lang, niche, cadence, note, added. Run the radar over the whole base in one line:

HANDLES=$(python3 -c "import json; d=json.load(open('references/watchlist.json')); print(','.join(c['handle'] for c in d['channels']))")
python3 scripts/yt_search.py --handles "$HANDLES" --by velocity --enrich --limit 8

Add a channel: resolve a video/link to its channel (yt-dlp <url> --print "%(channel)s|%(uploader_id)s|%(channel_id)s|%(channel_follower_count)s"), then append an object to channels[] (niche from recent titles, cadence from recent upload dates).

3. Transcript of a video

bash scripts/yt_transcript.sh "<youtube_url|id>" [text|json]

Transcripts go through TranscriptAPI.com v2 (a paid API — 100 free credits on signup, no card).

• Endpoint: GET https://transcriptapi.com/api/v2/youtube/transcript?video_url=<url|id>&format=text&include_timestamp=false&send_metadata=true
• Auth: Authorization: Bearer $TRANSCRIPT_API_KEY. Set the env var, or drop the key in ~/.claude/skills/yt-research/secrets/transcript-api-key.
• Use the v2 path with the video_url param (the old video_id path returns 404). Returns clean text + metadata (title, author). 1 credit per success.
• Errors: 401 bad key; 402 out of credits; 404 no captions on the video.

Then extract key points, compare competitors' narratives, and build the structure for your own video.

4. YouTube Data API v3 (optional, cleaner search)

Official path: search.list + videos.list + channels.list. Enable with --api, reads YOUTUBE_API_KEY from env.

export YOUTUBE_API_KEY=...
python3 scripts/yt_search.py "AI agents" --api --limit 20

Setup (once): in Google Cloud, enable YouTube Data API v3 → create an API key → export YOUTUBE_API_KEY. Free quota: 10,000 units/day (search.list = 100 units/request ≈ 100 searches/day). Without a key, search and stats still work fully via yt-dlp; only --api is unavailable.

Output

Default — a numbered list: views | velocity/day | duration — title + a channel — url line. With --json — an array of objects (id, title, channel, views, likes, comments, upload_date, velocity, url) for downstream analysis or writing to your base.

How to read it (content strategy)

• High velocity on a fresh video = a topic on the rise → candidate for your plan now.
• High absolute views on an old one = evergreen → a base topic, not urgent.
• Compare the winners' format / title / length — that's what works in the niche.
• Transcript of a top video → extract the structure and points; don't copy, do it better in your voice.

Limits & notes

• yt-dlp hits public data only — no private analytics of someone else's channel (only the owner has that).
• --enrich / --by velocity make one request per video — slower for big lists; run in batches.
• Private analytics of YOUR OWN channel needs OAuth (YouTube Analytics API) — separate setup.
• The channel base (references/watchlist.json) ships as a template — populate it with your niche.