video-use

video-use is a skill for Claude Code, Codex from S3YED/appie-kit. It costs 70 tokens per session (5,693 once invoked), scanned A, a copy of video-use, MIT.

A conversational video-editing workflow for transcribing footage, choosing cuts, changing colour, adding animated overlays, and burning in subtitles.

In plain words
What is it for?
Use it to edit interviews, tutorials, travel videos, talking-head recordings, and montages through an iterative review process.
Why use it?
It gives a structured way to decide on edits from the spoken content and visual material before changing the video.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/s3yed/appie-kit/video-use
Any agent
npx skills add S3YED/appie-kit --skill video-use
Clone the repo
git clone --depth 1 https://github.com/S3YED/appie-kit

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-use

README.md
[![agentmods](https://agentmods.dev/badge/skills/s3yed/appie-kit/video-use.svg)](https://agentmods.dev/skills/s3yed/appie-kit/video-use)
Your own site
<a href="https://agentmods.dev/skills/s3yed/appie-kit/video-use"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/video-use.svg" alt="Measured on agentmods" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,693 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00070 $0.05693
Opus 5 $0.00035 $0.02847
Sonnet 5 $0.00014 $0.01139
Haiku 4.5 $0.00007 $0.00569

Measured yesterday against content hash 37b24f7ec554, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

video-use 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 yesterday.

The scan reads SKILL.md. This mod also ships 7 executable files (helpers/grade.py, helpers/pack_transcripts.py, helpers/render.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to video-use — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/content/video-use/SKILL.md · 323 lines

How it starts

The opening of the file, as written. The whole thing — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Video Use

Principle

  1. LLM reasons from raw transcript + on-demand visuals. The only derived artifact that earns its keep is a packed phrase-level transcript (takes_packed.md). Everything else — filler tagging, retake detection, shot classification, emphasis scoring — you derive at decision time.
  2. Audio is primary, visuals follow. Cut candidates come from speech boundaries and silence gaps. Drill into visuals only at decision points.
  3. Ask → confirm → execute → iterate → persist. Never touch the cut until the user has confirmed the strategy in plain English.
  4. Generalize. Do not assume what kind of video this is. Look at the material, ask the user, then edit.
  5. Artistic freedom is the default. Every specific value, preset, font, color, duration, pitch structure, and technique in this document is a worked example from one proven video — not a mandate. Read them to understand what's possible and why each worked. Then make your own taste calls based on what the material actually is and what the user actually wants. The only things you MUST do are in the Hard Rules section below. Everything else is yours.
  6. Invent freely. If the material calls for a technique not described here — split-screen, picture-in-picture, lower-third identity cards, reaction cuts, speed ramps, freeze frames, crossfades, match cuts, L-cuts, J-cuts, speed ramps over breath, whatever — build it. The helpers are ffmpeg and PIL. They can do anything the format supports. Do not wait for permission.
  7. Verify your own output before showing it to the user. If you wouldn't ship it, don't present it.

Hard Rules (production correctness — non-negotiable)

These are the things where deviation produces silent failures or broken output. They are not taste, they are correctness. Memorize them.

  1. Subtitles are applied LAST in the filter chain, after every overlay. Otherwise overlays hide captions. Silent failure.
  2. Per-segment extract → lossless -c copy concat, not single-pass filtergraph. Otherwise you double-encode every segment when overlays are added.
  3. 30ms audio fades at every segment boundary (afade=t=in:st=0:d=0.03,afade=t=out:st={dur-0.03}:d=0.03). Otherwise audible pops at every cut.
  4. Overlays use setpts=PTS-STARTPTS+T/TB to shift the overlay's frame 0 to its window start. Otherwise you see the middle of the animation during the overlay window.
  5. Master SRT uses output-timeline offsets: output_time = word.start - segment_start + segment_offset. Otherwise captions misalign after segment concat.
  6. Never cut inside a word. Snap every cut edge to a word boundary from the Scribe transcript.
  7. Pad every cut edge. Working window: 30–200ms. Scribe timestamps drift 50–100ms — padding absorbs the drift. Tighter for fast-paced, looser for cinematic.
  8. Word-level verbatim ASR only. Never SRT/phrase mode (loses sub-second gap data). Never normalized fillers (loses editorial signal).
  9. Cache transcripts per source. Never re-transcribe unless the source file itself changed.
  10. Parallel sub-agents for multiple animations. Never sequential. Spawn N at once via the Agent tool; total wall time ≈ slowest one.
  11. Strategy confirmation before execution. Never touch the cut until the user has approved the plain-English plan.
  12. All session outputs in <videos_dir>/edit/. Never write inside the video-use/ project directory.

Read the full file on GitHub · 323 lines

Files

What ships with it

33 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. yesterday First seen · 323 lines · 70 tokens per session scan A 37b24f7ec554

Subscribe to this mod's changes

video-use is a skill published in the GitHub repository S3YED/appie-kit (7 stars, last pushed 9d ago), licensed MIT. It adds 70 tokens to every session and 5,693 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to video-use, differing in 0 lines, and is treated as a copy.

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