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.
npx skills add Galbaz1/video-research-mcp --skill video-explainergit 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/skills/galbaz1/video-research-mcp/video-explainer)<a href="https://agentmods.dev/skills/galbaz1/video-research-mcp/video-explainer"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/video-explainer/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/skills/galbaz1/video-research-mcp/video-explainer"><img src="https://agentmods.dev/badge/skills/galbaz1/video-research-mcp/video-explainer.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 | $0.00048 | $0.01341 |
| Opus 5 | $0.00024 | $0.00671 |
| Sonnet 5 | $0.00010 | $0.00268 |
| Haiku 4.5 | $0.00005 | $0.00134 |
Grade A, and why
video-explainer 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Explainer MCP — Tool Usage Guide
You have access to the video-explainer-mcp MCP server, which wraps the video_explainer CLI to synthesize explainer videos from text content.
Core Concept
This server is a synthesis companion to video-research-mcp. Research extracts knowledge; this server turns it into video. The pipeline is: content → script → narration → scenes → voiceover → storyboard → render.
Tool Selection Guide
| I want to... | Use this tool |
|---|---|
| Create a new video project | explainer_create |
| Feed content into a project | explainer_inject |
| Check project progress | explainer_status |
| List all projects | explainer_list |
| Run the full pipeline | explainer_generate |
| Run one pipeline step | explainer_step |
| Preview render (blocking) | explainer_render |
| Start background render | explainer_render_start |
| Check render progress | explainer_render_poll |
| Generate short-form video | explainer_short |
| Improve a step's output | explainer_refine |
| Add iterative feedback | explainer_feedback |
| Verify script accuracy | explainer_factcheck |
| Add sound effects | explainer_sound |
| Add background music | explainer_music |
Pipeline Order
Steps must run in order. Each step depends on the previous step's output:
1. script — Generate video script from input content
2. narration — Convert script to narration text
3. scenes — Generate scene descriptions
4. voiceover — Synthesize speech audio (TTS)
5. storyboard — Create visual storyboard
6. render — Combine into final video
Use explainer_generate to run all steps, or explainer_step for one at a time.
Content Injection
Before running the pipeline, inject content:
explainer_create(project_id="quantum-computing")
explainer_inject(
project_id="quantum-computing",
content="# Quantum Computing\n\nKey concepts:\n- Superposition...",
filename="research.md"
)
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.
- 9d ago First seen · 140 lines · 48 tokens per session scan A d3f310631f6e
video-explainer is a skill published in the GitHub repository Galbaz1/video-research-mcp (23 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 1,341 once invoked, about $0.0002 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.
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