mulmoterminal-video-edit

mulmoterminal-video-edit is a skill for Claude Code, Codex from receptron/mulmoterminal. It costs 147 tokens per session (3,522 once invoked), scanned A, original, MIT.

A command-line video editing workflow that uses plain-language instructions to cut, join, resize, or retime videos, change audio, and add subtitles or on-screen text. It uses ffmpeg for media processing and speech-recognition software for subtitles from speech.

In plain words
What is it for?
Use it to trim clips, combine videos, change speed or sound, make vertical video, create spoken-word subtitles, or add captions and titles.
Why use it?
It removes the need to write complex media-processing commands and provides a way to make common edits from a description.

Skill for Claude CodeCodex

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

Good fit Use it to trim clips, combine videos, change speed or sound, make vertical video, create spoken-word subtitles, or add captions and titles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/receptron/mulmoterminal/mulmoterminal-video-edit
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.

Any agent
npx skills add receptron/mulmoterminal --skill mulmoterminal-video-edit
Clone the repo
git clone --depth 1 https://github.com/receptron/mulmoterminal

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 mulmoterminal-video-edit

README.md
[![agentmods](https://agentmods.dev/badge/skills/receptron/mulmoterminal/mulmoterminal-video-edit/github.svg)](https://agentmods.dev/skills/receptron/mulmoterminal/mulmoterminal-video-edit)
Your own site
<a href="https://agentmods.dev/skills/receptron/mulmoterminal/mulmoterminal-video-edit"><img src="https://agentmods.dev/badge/skills/receptron/mulmoterminal/mulmoterminal-video-edit/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.

agentmods 80×15 button for mulmoterminal-video-edit

Your own site · 80×15
<a href="https://agentmods.dev/skills/receptron/mulmoterminal/mulmoterminal-video-edit"><img src="https://agentmods.dev/badge/skills/receptron/mulmoterminal/mulmoterminal-video-edit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 147 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,522 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.
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 $0.00147 $0.03522
Opus 5.5 $0.00059 $0.01409
Sonnet 5.5 $0.00029 $0.00704
Haiku 4.5 $0.00015 $0.00352

Measured 3d ago against content hash 41791c775678, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

mulmoterminal-video-edit 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 3d 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 -o "$models/ggml-large-v3-turbo.bin" https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin
server/skills/mulmoterminal-video-edit/SKILL.md · 235 lines

How it starts

The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Edit a video

The user points at a video and says what they want in plain words. They do not write ffmpeg commands; you do, in the terminal, and show them the result. Talk to them about their video — the part from 0:12 to 0:40, the subtitles, the title at the start — not about codecs and filters, unless they ask.

What you need

  • ffmpeg and ffprobe. Check with ffmpeg -version. If it is missing, say so and give the install command (brew install ffmpeg on a Mac); do not install it yourself.

  • For subtitles or captions drawn onto the picture, ffmpeg built with libass. Check: ffmpeg -hide_banner -filters | grep -E ' (subtitles|ass) ' prints two lines when it is.

  • For subtitles made from speech, whisper-cli from whisper.cpp (brew install whisper-cpp on a Mac; the same package MulmoTerminal's voice input uses) and a model. Look for one MulmoTerminal has already downloaded, in the workspace's models folder:

    ls "${CLAUDE_CWD:-$HOME/mulmoclaude}/models"/ggml-*.bin
    

    Use the file you find (prefer ggml-large-v3-turbo.bin when there are several) as $model below. If there is none, ask before downloading one, and say how big it is: ggml-large-v3-turbo.bin (about 1.6 GB, the most accurate) or ggml-small.bin (about 490 MB, faster, less accurate). Then put it in that folder, so voice input finds it too:

    models="${CLAUDE_CWD:-$HOME/mulmoclaude}/models" && mkdir -p "$models" &&
    curl -L -o "$models/ggml-large-v3-turbo.bin" https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3-turbo.bin
    

    (ggml-small.bin the same way.) Then $model is the file you downloaded.

  • showInPane, to open the result beside the terminal. In a project directory it exists only when Canvas was switched on before the session started. Without it, give the user the file's path.

The speech is transcribed on this machine. Never send the video or its sound anywhere.

Rules for every edit

  • Never change the original. Write a new file in the same folder, named after the original and the edit: talk.mp4 → talk-cut.mp4, talk-subtitled.mp4. If that name is taken, add a number. When the original is outside your working directory, write the new file in your working directory instead, so it can be shown.
  • Keep intermediate files in a working directory of their own (work=$(mktemp -d)), and give them plain names (audio.wav, subs.srt), which keeps the filter arguments below free of quoting.
  • Encode the result so it plays everywhere, the pane included: H.264 video, AAC sound, yuv420p, and the index at the front of the file.

Read the full file on GitHub · 235 lines

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. 3d ago First seen · 235 lines · 147 tokens per session scan A 41791c775678

Subscribe to this mod's changes

mulmoterminal-video-edit is a skill published in the GitHub repository receptron/mulmoterminal (245 stars, last pushed yesterday), licensed MIT. It adds 147 tokens to every session and 3,522 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-10-22.