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 eigent-ai/agent-skills --skill remotiongit clone --depth 1 https://github.com/eigent-ai/agent-skillsWrote 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/eigent-ai/agent-skills/remotion)<a href="https://agentmods.dev/skills/eigent-ai/agent-skills/remotion"><img src="https://agentmods.dev/badge/skills/eigent-ai/agent-skills/remotion.svg" alt="Measured on agentmods" 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 | $0.00065 | $0.01044 |
| Opus 5 | $0.00032 | $0.00522 |
| Sonnet 5 | $0.00013 | $0.00209 |
| Haiku 4.5 | $0.00006 | $0.00104 |
Grade A, and why
remotion 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 7d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Make videos programmatically — describe what you want and the skill writes the components, handles timing, animations, and renders to MP4. No video editor needed. Covers three workflows: React-based video composition, mathematical animation, and a full branded production pipeline.
Source Repository
- GitHub: remotion-dev/remotion
- Install upstream:
npx skills add remotion-dev/remotion
/remotion-video
Core skill. Takes a concept or script and produces a full Remotion React project — scenes, transitions, timing, and animations. Renders to MP4. Works for tutorials, product demos, social content, and data stories.
Workflow
- Clarify the video concept, duration, target format (landscape/portrait/square), and any brand colors or assets.
- Scaffold a Remotion project with
@remotion/cliif one doesn't exist. - Write React components for each scene — use
useCurrentFrame,interpolate, andspringfor timing and animation. - Wire scenes into a
Compositionwith correctdurationInFramesandfps. - Render to MP4 via
npx remotion render.
Example prompts
| Use case | Task prompt |
|---|---|
| Product demo | Create a 30-second product demo video for a password manager app. Show the browser extension detecting a login form, autofilling credentials, and a vault unlock animation. |
| Tutorial | Make a 60-second animated tutorial explaining how JWT authentication works. Use simple shapes and text animations, no talking head. |
| Social clip | Create a 15-second announcement video for our new feature launch. Bold text reveals, dark background, ends with the product logo and a CTA. |
/video-animation
Produces 3Blue1Brown-style mathematical and conceptual animations using Manim. Describe the concept and the skill plans scenes, writes the animation code, and iterates until the visual matches the explanation.
Workflow
- Understand the concept to animate — ask for the target audience and desired runtime if unclear.
- Break the explanation into discrete visual scenes (one idea per scene).
- Write Manim Python code for each scene using
ManimCEconventions. - Run scenes and review output; iterate on timing, labels, and transitions.
- Concatenate scenes into a final render.
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.
- 7d ago First seen · 95 lines · 0 tokens per session scan A b2a0c288d1f3
remotion is a skill published in the GitHub repository eigent-ai/agent-skills (19 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 65 tokens to every session and 1,044 once invoked, about $0.0003 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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