// Create professional multi-source news digest videos. Given a topic, autonomously finds YouTube news clips, tweets, and articles, then assembles a narrated video with voiceovers, background music, and broadcast-style text overlays using VideoDB.
Turn any research topic into a polished video with narration, dynamic visuals, and background music. Supports pluggable formats (briefing, fireship-explainer, and more). Researches via parallel subagents, scripts a narrative arc, sources real-world assets (stock footage, memes, logos) from APIs and a persistent VideoDB collection cache, produces assets, composes on a timeline, and self-reviews in a loop.
Create proof-first financial news recap videos using article proof, screenshots, charts, and selected VideoDB clips. Use when asked to build a daily market-news video, a proof-backed financial recap, or a news-to-video workflow.
| name | news-digest-video-agent |
| description | Create professional multi-source news digest videos. Given a topic, autonomously finds YouTube news clips, tweets, and articles, then assembles a narrated video with voiceovers, background music, and broadcast-style text overlays using VideoDB. |
Use this skill when the user wants to:
Before using this skill, ensure these dependencies are installed:
# Install VideoDB skill (provides video upload, indexing, search, TTS, timeline editing)
npx skills add video-db/skills
# Install Python SDK
pip install videodb python-dotenv
Set your API key (get one free at https://console.videodb.io):
export VIDEO_DB_API_KEY=your_key_here
# Install browser-use skill (provides screenshot, scroll recording, web page capture)
mkdir -p ~/.claude/skills/browser-use
curl -o ~/.claude/skills/browser-use/SKILL.md \
https://raw.githubusercontent.com/browser-use/browser-use/main/skills/browser-use/SKILL.md
Follow the browser-use SKILL.md instructions for any additional setup (e.g., playwright install).
from dotenv import load_dotenv
load_dotenv(".env")
import videodb
conn = videodb.connect()
print("VideoDB connected:", conn)
Strictly required:
Every URL, every fact, every piece of content MUST come from actual browser navigation.
Browser-use is your internet. It handles both discovery (searching Google, YouTube, Twitter) AND capture (screenshots, scroll recordings). There is no other search tool.
Every news digest follows the same structure:
Title card (4s) → Intro voiceover
→ News clip 1 (hook + clip) → News clip 2 (hook + clip) → News clip 3 (hook + clip)
→ Tweet transition → Tweet 1 → Tweet 2 → Tweet 3
→ Article transition → Article 1 → Article 2
→ Outro (5s)
Total: ~3-4 minutes (varies based on generated voiceover lengths)
Note: Only the title card (4s) and outro (5s) have fixed durations. Everything else is dynamically sized based on the actual voiceover durations returned by VideoDB TTS. The build_video.py template reads exact durations from registry.json — nothing is hardcoded.
The only required input is:
Optional:
assets/news-bg.jpg)assets/news-music.mp3)Use browser-use to actually browse the internet and gather real information:
<topic> news coverage 2024/2025/2026Do NOT write research from LLM memory. Every fact in research.md must trace back to a real URL you visited.
Save to outputs/<topic-slug>/data/research.md — include source URLs for every claim.
Use browser-use to navigate to YouTube and find real videos:
youtube.com → search <topic> BBC NewsPreferred YouTube channels to search:
Search strategy: Go to youtube.com and search for each channel + topic. Do NOT construct URLs from memory.
Criteria:
Save URLs to outputs/<topic-slug>/data/videos.json
For each of the 3 videos:
coll.upload(url=youtube_url)video.index_spoken_words(force=True)video.search(query)Update registry.json with video IDs, clip start times, and durations.
Use browser-use to visit X.com profiles of key figures and find real tweets:
x.com/<handle> (works without login in headless mode)platform.twitter.com/embed/Tweet.html?id=<ID>Note: X.com search (x.com/search?q=...) requires login and won't work. Stick to visiting profiles directly. See AGENTS.md Step 4 for the full workflow.
Do NOT create fake/placeholder tweet images. Every screenshot must be of a real tweet from a real browser session.
Save to outputs/<topic-slug>/assets/tweets/tweet_1.png, tweet_2.png, tweet_3.png
Upload each to VideoDB and update data/registry.json.
Use browser-use to find and capture real articles:
<topic> site:apnews.com (or other preferred sites)Preferred article sources (search these first):
Do NOT create fake scroll videos with ffmpeg from static images. The scroll must be a real browser recording of a real article.
Criteria:
Save to outputs/<topic-slug>/assets/articles/
Update data/registry.json.
Write 11 voiceover scripts based on research and collected sources:
| Script | Guideline | Content |
|---|---|---|
| intro | 2-3 sentences | Quick hook — what happened, why it matters |
| hook_1 | 1-2 sentences | Introduce news source 1, what they report |
| hook_2 | 1-2 sentences | Introduce news source 2, what they report |
| hook_3 | 1-2 sentences | Introduce news source 3, what they report |
| tweet_transition | 1-2 sentences | Bridge to social media reactions |
| tweet_1 | 2-3 sentences | Narrate tweet 1 content and context |
| tweet_2 | 2-3 sentences | Narrate tweet 2 content and context |
| tweet_3 | 2-3 sentences | Narrate tweet 3 content and context |
| article_transition | 1 sentence | Bridge to deep analysis section |
| article_1 | 3-4 sentences | Summarize article 1 key findings |
| article_2 | 3-4 sentences | Summarize article 2 key findings |
Tone: Professional broadcast news narrator. Concise, factual, no speculation.
Duration note: Do NOT target specific second counts. Write natural scripts following the sentence guidelines above. Generate via TTS, then record the exact duration returned by audio.length into registry.json. The build template handles all timing dynamically.
Generate each using VideoDB TTS: coll.generate_voice(text=script, voice_name="Default")
Save scripts to data/scripts.json. Update data/registry.json with audio IDs and exact durations (from audio.length).
Run the build template:
python templates/build_video.py outputs/<topic-slug>/data/registry.json
This assembles the 5-track timeline and generates the final stream URL.
Output saved to outputs/<topic-slug>/output/output.json.
All runs go inside outputs/ within the skill directory. Never create run folders at the skill root. Never place loose files at the topic folder root — everything goes in a subfolder.
agentic-video-creator/news-digest/
├── SKILL.md
├── AGENTS.md
├── README.md
├── assets/ # Shipped defaults (bg, music)
├── templates/
└── outputs/ # ALL runs go here
└── <topic-slug>/ # e.g., "epstein-files"
│
├── assets/ # Physical files (viewable media)
│ ├── tweets/ # Tweet screenshot PNGs
│ │ ├── tweet_1.png
│ │ ├── tweet_2.png
│ │ └── tweet_3.png
│ └── articles/ # Article scroll videos + screenshots
│ ├── article_1_scroll.mp4
│ ├── article_1_screenshot.png
│ ├── article_2_scroll.mp4
│ └── article_2_screenshot.png
│
├── data/ # Digital metadata (IDs, scripts, research)
│ ├── research.md # Topic research brief
│ ├── scripts.json # All 11 voiceover scripts
│ ├── registry.json # All VideoDB asset IDs + durations
│ └── videos.json # YouTube URLs + clip metadata
│
├── _build/ # Intermediate/working files (agent scratch)
│ └── ... # Upload results, processing logs, etc.
│
└── output/ # Final deliverables
└── output.json # Stream URL, player URL, duration
Rules:
assets/ = physical media files you can open and previewdata/ = metadata, IDs, scripts — everything VideoDB and the build template need_build/ = intermediate files created during processing (prefixed with _ to signal "ignore")output/ = the final video URL and metadataDefault background and music are in assets/:
assets/news-bg.jpg — Professional dark news backgroundassets/news-music.mp3 — News-style background music (125s, looped at 15% volume)Users can replace these with their own files. Upload to VideoDB and update registry.
A successful run produces:
output/output.json with playable stream URLassets/data/registry.json for reproducibilitySee outputs/ folder for complete agent-generated examples with full registry structure and asset organization.
Example output: Iran War 2026 Video
README.md — Overview, setup, and usage guideAGENTS.md — Detailed agent workflow, error handling, quality criteriatemplates/build_video.py — Timeline builder (reads registry.json)