Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/Galbaz1/video-research-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/galbaz1/video-research-mcp/explain-video)<a href="https://agentmods.dev/commands/galbaz1/video-research-mcp/explain-video"><img src="https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/explain-video/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/galbaz1/video-research-mcp/explain-video"><img src="https://agentmods.dev/badge/commands/galbaz1/video-research-mcp/explain-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.00594 |
| Opus 5 | $0.00009 | $0.00297 |
| Sonnet 5 | $0.00003 | $0.00119 |
| Haiku 4.5 | $0.00002 | $0.00059 |
Grade A, and why
explain-video scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Explain Video: $ARGUMENTS
Research a topic or analyze content, then synthesize it into an explainer video.
Parse Arguments
$ARGUMENTS should contain:
- A URL (YouTube, webpage) or topic to research
- A project ID for the explainer video
If only one argument, use it as both the research subject and derive the project ID.
Phase 1: Research & Analysis
Based on input type:
YouTube URL: Call video_analyze(url, instruction="Extract key concepts, structure, and talking points for creating an educational explainer video")
Webpage URL: Call content_analyze(url=url, instruction="Extract main topics, key facts, and narrative structure")
Topic text: Call research_deep(topic="<topic text — include research context for an educational explainer video. Focus on: key concepts, common misconceptions, real-world examples, and logical narrative flow>", scope="moderate")
Phase 2: Content Preparation
-
Synthesize the research output into a structured markdown document:
- Title and one-line summary
- Key concepts (bulleted)
- Narrative outline (numbered sections)
- Facts and statistics with sources
- Suggested visual metaphors
-
Create the explainer project:
explainer_create(project_id) -
Inject the content:
explainer_inject(project_id, content, "research.md")
Phase 3: Pipeline
Run the full pipeline: explainer_generate(project_id)
Check status with explainer_status(project_id) and report progress.
Phase 4: Preview Render
Render a preview: explainer_render(project_id, resolution="720p", fast=True)
Report the output location to the user.
Output
Summarize:
- Research findings (3-5 key points)
- Project location and status
- Render output path
- Suggestions for improvement (refine, sound, music)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 62 lines · 17 tokens per session scan A 515727d6d7c1
explain-video is a command published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 594 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
watch-video
Watch and analyze a video file or YouTube URL — extracts frames and audio for understanding.
zooza-setup
One-time Zooza setup — teaches Claude your business vocabulary so it understands your terms in every future session.
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