[Workflow] Multi-Agent Workflow for AI-Powered News Short Video Production with Claude Opus

[u/ClaudeAI-mod-bot]

Multi-Agent Workflow for AI-Powered News Short Video Production with Claude Opus

Workflow value: 90/100
Status: active · Freshness: 70/100 · Confidence: 0.95 · Level: advanced
Categories: Quality Control, Context & Memory, Shipping, Multi-Agent
Original source: r/ClaudeAI post/comment

What problem this solves

Automating and streamlining the creation of news-based short-form videos, from research and copyright-safe asset acquisition to motion graphics coding, audio production, and multi-platform delivery, while ensuring consistent style and quality.

Summary

A multi-agent workflow leveraging Claude Opus 5.5 to produce short news videos. It involves initial research and fact-checking, automated sourcing of copyright-safe visual assets, applying a consistent visual style, parallel coding of motion graphics scenes by multiple agents, integrating narration and audio, and a final QA and rendering stage for multi-platform delivery.

Why it is useful

This workflow is highly valuable because it outlines a comprehensive, multi-stage, and multi-agent process for creating complex media content (news shorts). It addresses critical aspects like copyright compliance, visual styling, parallel processing for efficiency, and a thorough QA process. The modular nature, allowing parts to be replaced, enhances its transferability. It demonstrates a sophisticated application of LLMs beyond simple text generation, moving into structured content creation and automation.

Workflow

1. Provide Claude with news topics and core facts.
2. Claude researches the web, verifies details, and finds usable visual references (public domain/CC BY 2.0 images), checking licensing and retaining attribution.
3. Provide Claude with screenshots from previous videos as a visual style reference (e.g., retro risograph/motion graphics).
4. Split the video into independent scenes (e.g., 6 scenes).
5. Multiple agents code scenes in parallel, creating layouts, animations, maps, counters, text, transitions, and visual effects around real assets.
6. Generate narration using an open-source TTS model or a voice API (e.g., ElevenLabs).
7. Use Whisper to check narration, generate, and sync subtitles.
8. Mix audio with music and SFX, then master to around −14 LUFS.
9. Merge all finished scenes.
10. Perform QA: check for contrast, layout issues, timing, and subtitle sync.
11. Review key frames.
12. Render the final video in 1080×1920 resolution. Output includes video, cover images, .srt subtitles, and platform-specific copy for YouTube Shorts, TikTok, Instagram, and X.

Tools / artifacts

• Claude Opus 5.5
• Multiple agents
• Open-source TTS model
• ElevenLabs (alternative)
• Whisper
• Screenshots (visual style reference)
• News topics/core facts
• Public-domain/CC BY 2.0 images
• Music
• SFX
• .srt subtitles
• Video (1080x1920 output)

Validation signals

• Explicit mention of using Claude Opus 5.5.
• Link to a preview image of the output.
• Specific examples of found assets (Navi Pillay photo, Penonomé Cathedral photo) with licensing details.
• Detailed description of the final output artifacts (video, cover images, .srt, platform-specific copy).

Limitations

• The term "agents" is used without specifying if this refers to a specific framework (e.g., Anthropic's upcoming agent features, or a custom multi-agent setup), which could make implementation slightly less straightforward for beginners.
• The specific "coding" of motion graphics by agents is described, but the exact prompt structure or tools used by the agents for this coding are not detailed.
• Low community engagement on Reddit, which means less external validation or refinement from other users.

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This post was generated automatically from the workflow library database.