Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/notque/vexjoy-agentnpx agentmods add skills/notque/vexjoy-agent/video-editingWrote 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/notque/vexjoy-agent/video-editing)<a href="https://agentmods.dev/skills/notque/vexjoy-agent/video-editing"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/video-editing/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/notque/vexjoy-agent/video-editing"><img src="https://agentmods.dev/badge/skills/notque/vexjoy-agent/video-editing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 139 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00020 | $0.02325 |
| Opus 5.5 | $0.00008 | $0.00930 |
| Sonnet 5.5 | $0.00004 | $0.00465 |
| Haiku 4.5 | $0.00002 | $0.00232 |
Grade A, and why
video-editing 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 25d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Video Editing Skill
Overview
This skill implements a 6-layer pipeline where AI handles judgment tasks (what to keep, what to cut, highlight selection) and FFmpeg/Remotion handle mechanical execution deterministically.
| Layer | Name | Mechanism | Primary Tool |
|---|---|---|---|
| 1 | CAPTURE | Inventory source footage | Bash + Glob |
| 2 | AI STRUCTURE | Transcript to EDL | LLM judgment |
| 3 | FFMPEG CUTS | EDL to segment files | FFmpeg (deterministic) |
| 4 | REMOTION COMPOSITION | Segments to TSX composition | Remotion + TypeScript |
| 5 | AI GENERATION | Fill gaps with generated assets | ElevenLabs / fal.ai (conditional) |
| 6 | FINAL POLISH | Human taste layer | Human + NLE |
Deep References
| Signal | Load | Content |
|---|---|---|
| Shell commands for each phase, gate checks | references/phase-commands.md |
Full command blocks for Phases 1-6 |
| FFmpeg recipes: cutting, concat, proxy, detection | references/ffmpeg-commands.md |
Timestamp extraction, batch cutting, audio normalization, scene/silence detection |
| Remotion composition scaffold | references/remotion-scaffold.md |
TSX composition template, render command, reuse patterns |
| Image-to-video pipeline | references/image-to-video.md |
Validate, prepare, encode, verify workflow |
| FFmpeg filter graphs for visualization | references/ffmpeg-filters.md |
Scale/pad, showwaves, showspectrum, overlay, complete filter graphs |
Instructions
Preflight (Run before Phase 1)
Hard requirements (BLOCK if missing): ffmpeg (all phases), node (Remotion / npx).
Soft requirements (WARN if missing): remotion (only required for Phase 4).
which ffmpeg >/dev/null 2>&1 || { echo "ERROR: ffmpeg not found. Install: brew install ffmpeg (macOS) | apt install ffmpeg (Linux)"; exit 1; }
which node >/dev/null 2>&1 || { echo "ERROR: node not found. Install: https://nodejs.org or via nvm"; exit 1; }
npx remotion --version >/dev/null 2>&1 || echo "WARNING: remotion CLI not found. Phase 4 unavailable. Install: npm install @remotion/cli"
What ships with it
5 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.
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.
- 26d ago Changed · -149 lines · +8 tokens per session 53873d548701
- 27d ago Changed · +4 lines 29777852475e
- 1mo ago First seen · 196 lines · 20 tokens per session scan A dc33100c2dd2
video-editing is a skill published in the GitHub repository notque/vexjoy-agent (442 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 2,325 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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