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 agentmods add skills/shaom/infocard-video-skills/remotion-video-workflownpx skills add shaom/infocard-video-skills --skill remotion-video-workflowgit clone --depth 1 https://github.com/shaom/infocard-video-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/shaom/infocard-video-skills/remotion-video-workflow)<a href="https://agentmods.dev/skills/shaom/infocard-video-skills/remotion-video-workflow"><img src="https://agentmods.dev/badge/skills/shaom/infocard-video-skills/remotion-video-workflow.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 | $0.00050 | $0.01510 |
| Opus 5 | $0.00025 | $0.00755 |
| Sonnet 5 | $0.00010 | $0.00302 |
| Haiku 4.5 | $0.00005 | $0.00151 |
Grade A, and why
remotion-video-workflow 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 6d 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 — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Remotion Video Workflow
Overview
Use this skill to turn a brief, article, notes, or other source material into a structured Remotion short video workflow. This skill is designed for reusable production, not for one-off visual experiments.
The default target is a knowledge-oriented short video with clear pacing, stable structure, and linked video and cover outputs.
The validated baseline for v1 is a 30fps Remotion project with:
- a pure data storyboard module
- a separate cover content module
- one or more video compositions in
Root.tsx - one still composition for the cover
- tests that enforce structure and content preservation
- render and
ffprobevalidation
This skill assumes the agent also follows the upstream remotion-best-practices skill for Remotion-specific implementation details.
Use that upstream skill for:
- composition and still registration
- frame-driven animation rules
TransitionSeriesusage- audio component behavior
- sequencing rules
- font loading behavior
When To Use
Use this skill when the user wants:
- a knowledge-dense short video
- a Hook / Content / End Card structure
- a Remotion-based workflow instead of a generic script-only answer
- a cover and video that should feel related
- ratio-aware output such as
3:4or4:3 - render and output validation as part of the task
Do not use this skill as the default choice for:
- a single throwaway animation experiment
- long-form narrative videos
- narration-first talking-head edits
- pure video editing tasks that do not need Remotion composition
Input Expectations
Collect or infer these inputs:
- source material or topic
- target ratio
- target runtime
- brand inputs if any
- cover requirement
- output requirement such as plan only, implementation, render, or verification
When inputs are missing, infer conservatively:
- default ratio:
3:4 - default fps:
30 - default runtime target:
25to45seconds - default structure:
Hook -> Content -> End Card - default visual mode: one reusable theme with one warm accent and one cool accent
- default output mode: planning first, implementation second
What ships with it
14 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/openai.yaml 111 B
- README.md 800 B
- references/audio.md 2.3 KB
- references/branding.md 1.8 KB
- references/cover-linkage.md 1.8 KB
- references/layout-ratios.md 2.2 KB
- references/quality-checklist.md 1.3 KB
- references/render-pipeline.md 1.7 KB
- references/video-structure.md 2.6 KB
- references/workflow-overview.md 2.8 KB
- scripts/probe_output.sh 374 B runs code
- scripts/render_cover.sh 336 B runs code
- scripts/render_video.sh 373 B runs code
- scripts/run_checks.sh 341 B runs code
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.
- 6d ago First seen · 210 lines · 50 tokens per session scan A 0c6c45fe1811
remotion-video-workflow is a skill published in the GitHub repository shaom/infocard-video-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 1,510 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 2026-08-31.
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