video-editing-pro

video-editing-pro is a skill for Claude Code, Codex from S3YED/appie-kit. It costs 29 tokens per session (10,476 once invoked), scanned A, original, MIT.

A decision guide for editing short videos in which someone speaks to the camera, such as TikToks, Reels, and YouTube Shorts. It focuses on choosing the opening, removing filler, setting the pace, and checking viewer retention.

In plain words
What is it for?
Use it to select a strong hook, remove silence and filler, improve pacing, and judge whether a talking-head edit holds attention.
Why use it?
It helps editors decide what to keep and cut when the raw recording is too long, slow, or unclear.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is node scripts/transcribe.mjs # uses @remotion/install-whisper-cpp, outputs captions.json.

Good fit Use it to select a strong hook, remove silence and filler, improve pacing, and judge whether a talking-head edit holds attention.

Compare 6 skills from other repositories ↓
Install

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.

Clone the repo
git clone --depth 1 https://github.com/S3YED/appie-kit
agentmods
npx agentmods add skills/s3yed/appie-kit/video-editing-pro

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for video-editing-pro

README.md
[![agentmods](https://agentmods.dev/badge/skills/s3yed/appie-kit/video-editing-pro.svg)](https://agentmods.dev/skills/s3yed/appie-kit/video-editing-pro)
Your own site
<a href="https://agentmods.dev/skills/s3yed/appie-kit/video-editing-pro"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/video-editing-pro.svg" alt="Measured on agentmods" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 10,476 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 4 findings, 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 630
    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]
  • medium MCP Rug Pull · line 639
    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]
  • medium MCP Rug Pull · line 668
    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]
  • medium MCP Rug Pull · line 669
    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]
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00029 $0.10476
Opus 5 $0.00015 $0.05238
Sonnet 5 $0.00006 $0.02095
Haiku 4.5 $0.00003 $0.01048

Measured 4d ago against content hash 9751d6f271b2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

video-editing-pro scanned grade A with 1 finding 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 4d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl -L "https://cdn.mixkit.co/sfx/download/mixkit-fast-small-sweep-transition-166.wav" -o sfx/whoosh-1.wav
skills/content/video-editing-pro/SKILL.md · 690 lines

How it starts

The opening of the file, as written. The whole thing — 690 lines — stays where its author put it; the contents beside it link to each section on GitHub.

video-editing-pro Skill

Purpose

Decision-level framework for cutting talking-head short-form video (Reels/Shorts/TikTok). Not tool instructions — cut decisions: which sentences survive, where to end them, how to pick the hook, how to pace energy, and how to know when you got it wrong. Codified from auto-editor source defaults, production-audio practitioner interviews, platform retention data, and analysis of the 2026-05-03 content factory clips.


Source

Every entry consumed directly, not cited generically:

Source URL What it gave
auto-editor reference https://auto-editor.com/ref/edit Exact defaults: threshold=0.04 (normalized amplitude), margin=0.2s padding, smooth=0.2s,0.1s
auto-editor options https://auto-editor.com/options --margin 0.2s default, --smooth 0.2s,0.1s (mincut 0.2s, minclip 0.1s)
auto-editor blog: threshold removal https://auto-editor.com/blog/silent-threshold Why 0.04 is the amplitude default, not dB
Production Expert: René Coronado interview edit https://www.production-expert.com/production-expert-1/2020/7/29/editing-audio-interviews-what-choices-do-we-make-and-why "My goal is NOT to get from 14s to 6s" — clarity-of-thought frame vs duration-reduction frame
podmuse.com: pro podcast edit workflow https://www.podmuse.com/post/edit-audio-for-podcast Selective filler removal rule: cut fillers that block clarity or stack awkwardly, leave ones that "sound human and disappear in context"
Recut silence removal docs https://getrecut.com/remove-silence-from-video-automatically Padding 0.4–0.5s sounds natural; 0s creates rapid-fire effect
Aibrify: YouTube Shorts retention curve playbook 2026 https://aibrify.com/blog/youtube-shorts-retention-curve-playbook Pacing target 1.5–2s per visual change; below 1.2s = noise, above 2.5s = dip; 55–70% retention for talking-head
TikTok editing guide https://edicionvideopro.com/en/editing-for-platforms-video-marketing/tiktok-video-editing-guide/ "Every pause between sentences, every transitional phrase should be cut"; drop-off graph as diagnostic
Postigniter: hook formulas https://postigniter.com/blog/high-performance-hooks-writing-scroll-stopping-intros-for-short-form-video Optimal hook 1.5–3s; 0.1–0.3s cuts for dynamism in hook window
go-viral.app: first 3 seconds https://www.go-viral.app/blog/hook-first-3-seconds/ <50% retention at 3s = hook failing; >70% = strong; target >70%
autoshorts.app: hooks 2026 https://www.autoshorts.app/blog/instagram-reels-hooks-2026 3+ cuts in first 3s boost watch time 58%; each cut creates "change signal"
VlogLikePro: energy management http://vloglikepro.com/editing-styles-that-drive-watch-time-beyond-basics Energy curve; cut every 4s→3s→2s building to reveal; 10–15s micro-hook cadence
We Design Motion: attention without faster cuts https://wedesignmotion.com/blog/design/video-content-that-earns-attention-without-faster-cuts/ 5-layer attention model: promise→clarity→progression→contrast→craft
socialync.io: hook-body-payoff structure https://www.socialync.io/blog/short-form-video-structure-guide-2026 "8 seconds without visual change = viewer exit"; tension > rush to resolution
Ascynd: Hormozi captions breakdown https://ascynd.io/en/blog/hormozi-captions One keyword per phrase; noun or verb carrying meaning; yellow #FFD93D; 200–500ms per word timing
reelwords.ai: caption retention https://reelwords.ai/blog/how-to-add-captions-to-short-form-video Highlight: promise words, contrast words, specificity (numbers/outcomes), stakes words; never highlight "the", "and", "like"
Film Editing Pro: reviewing your own cuts https://filmeditingpro.com/3-editing-tips-for-reviewing-your-own-cuts Audio-off test; black-and-white test; Hitchcock rule; first-reaction markers
joelv.ca: post-edit fresh-eyes technique https://joelv.ca/blog/best-way-to-edit-better Watch with someone beside you = best fresh-eyes; Joe Walker (Dune) black-and-white review trick
autocut.com: finding viral moments https://autocut.com/en/blogs/viral-moment/ Three criteria for clip viability: hook (curiosity), clarity (standalone), emotion (tension/surprise/reaction)

Read the full file on GitHub · 690 lines

Files

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.

Changes

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.

  1. 4d ago First seen · 690 lines · 29 tokens per session scan A 9751d6f271b2

Subscribe to this mod's changes

video-editing-pro is a skill published in the GitHub repository S3YED/appie-kit (7 stars, last pushed 12d ago), licensed MIT. It adds 29 tokens to every session and 10,476 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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