How do I install the Multi Video Synthesis skill?

Run npx skillmds add thedixitjain/multi-video-synthesis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Multi Video Synthesis safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Multi Video Synthesis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Multi Video Synthesis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Multi Video Synthesis?

thedixitjain (@thedixitjain) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Multi Video Synthesis by thedixitjain

Name: Multi Video Synthesis
Rating: 4.2 (5 reviews)
Author: thedixitjain

File contents

Skill: Autonomous Multi-Video Synthesis Pipeline

Objective: (ATTENTION GUARDIAN) Perform a high-density Targeted Extraction across a massive amount of video content (10+ videos) to extract the absolute truth, map the semantic landscape, and save the user from hour-long research.

Execution Steps:

Broad Search: Use search_youtube with max_results=15 to cast a wide net across the topic.
RoA Filtering (MANDATORY):
- Fetch details for ALL videos using get_video_details.
- Calculate engagement metrics with calculate_engagement_metrics.
- Identify the top 10 videos that have the highest "Return on Attention" (high engagement, relevant keywords, authoritative channels).
- Explicitly tell the user which videos you are ignoring and why (e.g., "Filtering out 5 videos that appear to be clickbait/low-engagement").
Massive Ingestion:
- For the top 10 videos, attempt to retrieve all transcripts using get_video_transcript.
- If any transcripts are unavailable, use get_video_details to read their metadata and descriptions as a high-signal fallback.
Semantic Mapping & Synthesis:
- Cross-reference all transcripts simultaneously.
- Map the "Semantic Vectors": Identify the Consensus (arguments shared by 3+ creators), the Controversies (conflicting viewpoints), and the Hidden Gems (unique insights mentioned by only one expert).
Precision Targeting:
- For every major argument or insight in your synthesis, you MUST provide at least one direct ?t=... jump-link using generate_timestamp_url.
Unified Report Delivery:
- Provide a structured "Multi-Video Intelligence Briefing".
- Include a "Consensus vs. Controversy" table.
- Provide a "Clips of Interest" list with direct timestamp URLs.
- Always ask if the user wants to see a visualization of these findings (e.g., a chart of creator sentiment) or publish this to a shareable HTML report.

Key Design Principle: You are the orchestrator of this pipeline. You are not just summarizing videos; you are synthesizing a new, high-density knowledge artifact that does not exist elsewhere on the web.

Source: google/adk-samples → python/agents/youtube-analyst/youtube_analyst/skills/multi-video-synthesis/SKILL.md

---name: multi-video-synthesisdescription: Performs high-density targeted extraction across 10+ videos to map semantic landscapes, consensus, and controversies.---### Skill: Autonomous Multi-Video Synthesis Pipeline**Objective**: (ATTENTION GUARDIAN) Perform a high-density **Targeted Extraction** across a massive amount of video content (10+ videos) to extract the absolute truth, map the semantic landscape, and save the user from hour-long research.**Execution Steps**:1. **Broad Search**: Use `search_youtube` with `max_results=15` to cast a wide net across the topic. 2. **RoA Filtering (MANDATORY)**: - Fetch details for ALL videos using `get_video_details`. - Calculate engagement metrics with `calculate_engagement_metrics`. - Identify the top 10 videos that have the highest "Return on Attention" (high engagement, relevant keywords, authoritative channels). - Explicitly tell the user which videos you are ignoring and why (e.g., "Filtering out 5 videos that appear to be clickbait/low-engagement").3. **Massive Ingestion**: - For the top 10 videos, attempt to retrieve all transcripts using `get_video_transcript`. - If any transcripts are unavailable, use `get_video_details` to read their metadata and descriptions as a high-signal fallback.4. **Semantic Mapping & Synthesis**: - Cross-reference all transcripts simultaneously. - Map the "Semantic Vectors": Identify the **Consensus** (arguments shared by 3+ creators), the **Controversies** (conflicting viewpoints), and the **Hidden Gems** (unique insights mentioned by only one expert).5. **Precision Targeting**: - For every major argument or insight in your synthesis, you MUST provide at least one direct `?t=...` jump-link using `generate_timestamp_url`.6. **Unified Report Delivery**: - Provide a structured "Multi-Video Intelligence Briefing". - Include a "Consensus vs. Controversy" table. - Provide a "Clips of Interest" list with direct timestamp URLs. - Always ask if the user wants to see a visualization of these findings (e.g., a chart of creator sentiment) or publish this to a shareable HTML report.**Key Design Principle**: You are the orchestrator of this pipeline. You are not just summarizing videos; you are synthesizing a new, high-density knowledge artifact that does not exist elsewhere on the web.---**Source:** [`google/adk-samples`](https://github.com/google/adk-samples) → `python/agents/youtube-analyst/youtube_analyst/skills/multi-video-synthesis/SKILL.md`

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