News Digest Video Agent

News Digest Video Agent Skill

Use this skill when the user wants to:

• Create a news digest video on any topic
• Turn a breaking news story into a multi-perspective video summary
• Combine YouTube clips, tweets, and articles into a professional broadcast-style video

Setup (run once)

Before using this skill, ensure these dependencies are installed:

1. VideoDB skill & SDK

# 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

2. Browser use skill

# 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).

3. Verify setup

from dotenv import load_dotenv
load_dotenv(".env")
import videodb
conn = videodb.connect()
print("VideoDB connected:", conn)

Required tools / capabilities

Strictly required:

• VideoDB skill — video upload, indexing, search, TTS, timeline editing
• Browser use skill — ALL internet research, searching, screenshots, scroll recordings
• File read/write — manage registry, scripts, and output files
• Bash / Python — run the build script

CRITICAL: No Hallucinated Data

Every URL, every fact, every piece of content MUST come from actual browser navigation.

• You MUST use browser-use to visit real websites and find real URLs
• You MUST NOT generate YouTube URLs from memory — go to youtube.com and search
• You MUST NOT create fake tweet images — go to Twitter/X and screenshot real tweets
• You MUST NOT write research from LLM knowledge alone — browse real articles first
• If browser-use is not working, STOP and tell the user. Do NOT proceed with made-up data.

Browser-use is your internet. It handles both discovery (searching Google, YouTube, Twitter) AND capture (screenshots, scroll recordings). There is no other search tool.

Video Structure (fixed, deterministic)

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.

Inputs

The only required input is:

• topic — e.g., "iran war", "claude source code leak", "us tariffs china"

Optional:

• Custom background image (default: shipped assets/news-bg.jpg)
• Custom background music (default: shipped assets/news-music.mp3)

Workflow

Step 1: Research the topic (USE BROWSER-USE)

Use browser-use to actually browse the internet and gather real information:

1. Open Google → search <topic> news coverage 2024/2025/2026
2. Visit 2-3 top results from trusted news sites
3. Read the actual article content
4. Extract key facts: what happened, who's involved, timeline, impact

Do 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.

Step 2: Find 3 YouTube news videos (USE BROWSER-USE)

Use browser-use to navigate to YouTube and find real videos:

1. Open youtube.com → search <topic> BBC News
2. Click on a real result → copy the URL from the browser
3. Repeat for 2 more channels

Preferred YouTube channels to search:

• Al Jazeera English
• BBC News
• CNN
• Reuters
• CNBC
• DW News
• Sky News
• PBS NewsHour

Search strategy: Go to youtube.com and search for each channel + topic. Do NOT construct URLs from memory.

Criteria:

• 3 different news sources for diverse perspectives
• Recent and relevant to the topic
• 2-15 minutes long, English language
• Each should present a distinct "take" or angle
• Every URL must come from actually visiting youtube.com — not from LLM knowledge

Save URLs to outputs/<topic-slug>/data/videos.json

Step 3: Process YouTube videos with VideoDB

For each of the 3 videos:

1. Upload to VideoDB: coll.upload(url=youtube_url)
2. Index spoken words: video.index_spoken_words(force=True)
3. Semantic search for the best ~25 second clip: video.search(query)
4. Select a clip that is self-contained, ends at a natural sentence, and shows the channel's perspective

Update registry.json with video IDs, clip start times, and durations.

Step 4: Capture 3 tweet screenshots (USE BROWSER-USE)

Use browser-use to visit X.com profiles of key figures and find real tweets:

1. Visit public profiles directly: x.com/<handle> (works without login in headless mode)
2. Find 3 tweets from notable people with different perspectives
3. Screenshot each tweet via the embed endpoint: 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.

Step 5: Capture 2 article assets (USE BROWSER-USE)

Use browser-use to find and capture real articles:

1. Open Google → search <topic> site:apnews.com (or other preferred sites)
2. Visit the actual article in the browser
3. Screenshot the key section (chart, data, key quote)
4. Record a scroll video (~8-13 seconds) by scrolling through the article

Preferred article sources (search these first):

• AP News (apnews.com)
• Council on Foreign Relations (cfr.org)
• Reuters (reuters.com)
• BBC News (bbc.com/news)
• The Guardian (theguardian.com)
• NPR (npr.org)

Do NOT create fake scroll videos with ffmpeg from static images. The scroll must be a real browser recording of a real article.

Criteria:

• Article 1: economic/domestic impact angle
• Article 2: historical context / geopolitical analysis angle

Save to outputs/<topic-slug>/assets/articles/ Update data/registry.json.

Step 6: Write scripts & generate voiceovers

Write 11 voiceover scripts based on research and collected sources:

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).

Step 7: Build the video

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.

Per-run folder structure

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 preview
• data/ = 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 metadata
• Zero files at the topic root — everything in a subfolder

Shipped assets

Default background and music are in assets/:

• assets/news-bg.jpg — Professional dark news background
• assets/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.

Deliverables

A successful run produces:

• output/output.json with playable stream URL
• All physical media preserved in assets/
• Full data/registry.json for reproducibility

Reference

See outputs/ folder for complete agent-generated examples with full registry structure and asset organization.

Example output: Iran War 2026 Video

Reference docs

• README.md — Overview, setup, and usage guide
• AGENTS.md — Detailed agent workflow, error handling, quality criteria
• templates/build_video.py — Timeline builder (reads registry.json)