B-roll Finder (real footage from YouTube)

The found-footage counterpart of broll-generator. Where broll-generator synthesizes B-roll with an AI model, broll-finder finds real public YouTube footage about a topic or person (e.g. Anthony Bourdain), downloads only the relevant windows, and normalizes them into the same clean 9:16, silent, manifest-backed clips that avatar-reel-composer lays under an avatar voice-over.

Key difference from broll-generator: that one forbids the presenter on screen. Here the footage often should show the subject (Bourdain himself in a market) — found B-roll can contain real people and the subject.

It is an orchestrator built on existing skills' patterns: reel-discovery (search), youtube-audio-toolkit / video-transcribe (transcripts), youtube-videos (yt-dlp download) and broll-generator (manifest + ffmpeg normalization).

⚠️ Rights / licensing (read first)

Third-party YouTube footage is copyrighted. This skill records the license of every clip and labels it:

• Creative Commons (--creative-commons) → reuse generally allowed with attribution to the original channel. Safer for a published reel; still verify per video and credit the source.
• Standard YouTube license (default) → NOT cleared for republishing. Treat those clips as reference / research only. Using them in a published reel may infringe copyright unless it qualifies as fair use or you get permission. The manifest flags each clip reusable: false with a rights_note.

When in doubt, run with --creative-commons.

Setup

pip3 install -r ~/.cursor/skills/broll-finder/scripts/requirements.txt

yt-dlp + ffmpeg/ffprobe must be on PATH (already installed in this repo). A YouTube Data API key is optional: set YT_API_KEY (or reuse reel-discovery's config.json) for exact view counts and a real Creative-Commons search filter; without it, search degrades to yt-dlp ytsearch. No Replicate token is needed — search + download are free.

Pipeline (idempotent, with one agent checkpoint)

query (topic/person)  [+ optional --creative-commons]
  │
1 search.py       ─► <work>/candidates.json + candidates.md          (ranked)
  │
2 transcripts.py  ─► <work>/transcripts/<id>.{json,md}               (timecoded, NO download)
  │                  <work>/selection.template.json                  (skeleton)
  │
  ▼  ── CHECKPOINT: agent reads candidates.md + transcripts/*.md, then writes
  │     selection.json with the [start,end] windows worth cutting ──
  │
3 cut_segment.py  ─► <avatar>/broll/found/<NNN>_<slug>.mp4 + manifest.json
                     (downloads ONLY each window, crops to 9:16, strips audio,
                      records source + license + rights_note)

The relevance "engine" is the agent reading timecoded transcripts and (optionally) review frames — exactly the agent-in-the-loop pattern of video-scene-analysis and create_avatar.py. Two complementary signals: what is said (transcript → candidate window, cheap, no download) and what is shown (review the --frames jpg or run video-scene-analysis to confirm the shot is usable footage, not a chyron'd interview).

Quick start (orchestrated)

# from the repo root so <avatar>/... paths resolve
python3 .cursor/skills/broll-finder/scripts/find_broll.py \
    --query "anthony bourdain street food vietnam" \
    --avatar-dir lolo --max-candidates 8 --lang en --creative-commons --frames

This searches + fetches transcripts, then stops at the checkpoint and prints where to look. Then:

1. Skim found-broll/<slug>/candidates.md and found-broll/<slug>/transcripts/*.md.
2. Copy selection.template.json → selection.json and edit it: keep the windows you want, set real start/end (seconds, from the mm:ss markers) and a description per clip; add/remove entries from any candidate.
3. Re-run the exact same command — finished stages are skipped and stage 3 cuts the clips into <avatar>/broll/found/.

--status prints stage progress without doing work. --force-search / --force-transcripts re-run a stage.

selection.json

{
  "segments": [
    { "url": "https://youtu.be/VIDEOID", "start": 132, "end": 138,
      "description": "Bourdain comiendo pho en un puesto callejero de Hanoi", "fit": "crop" },
    { "url": "https://youtu.be/OTHERID", "start": 41.5, "end": 47,
      "description": "mercado nocturno, vapor de los puestos, multitud", "fit": "blur" }
  ]
}

Single clip (workhorse, like generate_broll.py)

# from YouTube — downloads ONLY 02:12–02:18, saves into the avatar's broll/found/
python3 .cursor/skills/broll-finder/scripts/cut_segment.py \
    --url "https://youtu.be/VIDEOID" --start 132 --end 138 \
    --description "Bourdain comiendo pho en un puesto callejero de Hanoi" \
    --avatar-dir lolo --fit crop --frame

# from an already-downloaded local file
python3 .cursor/skills/broll-finder/scripts/cut_segment.py \
    --input footage.mp4 --start 5 --end 11 --description "olas al atardecer" --fit blur

Output: <avatar>/broll/found/<NNN>_<slug>.mp4 + a manifest.json entry; a JSON summary (path, dims, license, source_url, segment) is printed to stdout.

16:9 → 9:16 (--fit)

YouTube is mostly 16:9; reels are 9:16. The rule / default is a center crop-to-fill — the source is scaled UP until it covers the whole 9:16 frame (preserving aspect), then center-cropped. The result fills the ENTIRE frame; there is never any letterbox/pillarbox padding of a scaled-down copy.

• crop (default, recommended) — center crop-to-fill that covers the whole 9:16 frame. No black bars, ever. Best for talking subjects and most footage.
• pad — opt-in only. Letterbox with black bars (keeps the whole 16:9 frame).
• blur — opt-in only. Fits the frame over a blurred, enlarged copy of itself (soft backfill instead of hard bars).

Only switch away from crop deliberately, for a specific shot where center cropping would cut out essential content (e.g. a wide landscape or on-screen text near the edges).

Handoff to avatar-reel-composer

Found clips are drop-in B-roll. In the storyboard, set a broll scene to use an existing clip instead of generating one:

{
  "id": "s3", "type": "broll", "broll_source": "existing",
  "broll_clip": "lolo/broll/found/001_bourdain-pho-hanoi.mp4",
  "text": "viajar te cambia la forma de ver el mundo"
}

compose_reel.py uses the clip as-is (looping a too-short silent clip to cover its slot, then trimming) and keeps the avatar's single master narration in sync. Use --frames + the manifest's rights_note to vet each clip before publishing.

Scripts

Anti-patterns

1. Do not publish standard-license clips without clearing rights — they are reusable: false (reference only). Prefer --creative-commons for publishing.
2. Do not download whole videos to find a 6s window — transcripts are fetched first (free, no download) so only the chosen sections are downloaded.
3. Do not scan dozens of long videos — cap with --max-candidates and --max-duration; skim transcripts before cutting.
4. Do not letterbox a 16:9 clip into 9:16 by default — the default is center crop-to-fill that covers the whole frame (no black bars). Switch to --fit blur/pad only deliberately, for a wide/landscape shot where cropping would cut out essential content.
5. Do not commit found-broll/ or large clips — add them to .gitignore (research output + third-party media).
6. Do not forget attribution for Creative-Commons clips — credit the channel (channel / source_url are in the manifest).

Troubleshooting

• youtube-transcript-api failed then "falling back to yt-dlp subtitles" — normal. The captions API is often IP-blocked; the yt-dlp VTT fallback still produces the timecoded transcript.
• No supported JavaScript runtime / impersonation warnings from yt-dlp — warnings, not errors; section download and subtitle fetch still work. If a download fails, update yt-dlp (pip3 install -U yt-dlp) and/or install a JS runtime (deno) per the yt-dlp wiki.
• "Sign in to confirm you're not a bot" / age-gate — add --cookies-from-browser firefox (the browser where you're logged into YouTube).
• No candidates — set YT_API_KEY for real search, drop --creative-commons, or broaden the --query.

Additional resources

• Usage walkthrough: examples.md
• Synthetic counterpart: broll-generator. Consumer: avatar-reel-composer (broll_source: existing). Discovery at scale: reel-discovery.