Video Edit logo

Video Edit

Organization
genmedia-labs
video-edit

Edit existing video on RunComfy — this skill is a smart router that matches the user's intent to the right edit model in the RunComfy catalog. Picks Wan 2.7 Edit-Video (general restyle / background swap / packaging swap, identity + motion preservation), Kling 2.6 Pro Motion Control (transfer precise motion from a reference video to a target character), or Lucy Edit Restyle (lightweight identity-stable restyle / outfit swap). Bundles each model's documented prompting patterns so the skill gets sharper edits without burning iterations on the wrong model. Calls `runcomfy run <vendor>/<model>/<endpoint>` through the local RunComfy CLI. Triggers on "video edit", "edit video", "restyle video", "swap video background", "motion control", "outfit swap video", or any explicit ask to transform a video.

Overview

Publishergenmedia-labs
Repositoryskills
Skill namevideo-edit
Stars
26
Forks
12
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by genmedia-labs on GitHub. Read the source before you install it.

Installation

Install the Video Edit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/genmedia-labs/skills/tree/main/video-edit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/genmedia-labs/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/video-edit .claude/skills/video-edit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Video Edit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Video Edit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Video Edit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Video Edit — Pro Pack on RunComfy

runcomfy.com · Wan 2.7 Edit-Video · Kling Motion-Control Pro · Lucy Edit Restyle · GitHub

Video edit, intent-routed. This skill doesn't lock you to one model — it picks the right video-edit model in the RunComfy catalog based on what the user actually wants: general restyle, motion transfer from a reference clip, or lightweight identity-stable outfit / background swap.

bash
npx skills add agentspace-so/runcomfy-skills --skill video-edit -g

Pick the right model for the user's intent

User intentModelWhy
Restyle a talking-head video — preserve face / pose / lip movementWan 2.7 Edit-VideoStrong identity + motion preservation; supports up to 1080p
Swap product background, keep camera motionWan 2.7 Edit-VideoCamera motion preserved; one-direction edit honored
Replace packaging design using a reference imageWan 2.7 Edit-Video + reference_imageReference-conditioned design transfer
Apply cinematic color grade / commercial polishWan 2.7 Edit-VideoGood at single-direction global look changes
Transfer precise motion from a reference video to a target characterKling 2.6 Pro Motion ControlDesigned for motion mapping with identity hold
Lip-sync motion of a target character to source video's lip movementKling 2.6 Pro Motion ControlBuilt for tight temporal coherence
Lightweight outfit / costume swap with identity preservationLucy Edit RestyleCore strength is localized identity-stable edits
Identity-stable restyle ("astronaut in desert", "warm golden-hour lighting")Lucy Edit RestyleSpecializes in temporal consistency for restyle
Default if unspecifiedWan 2.7 Edit-VideoMost versatile, highest resolution

The agent reads this table, classifies the user's intent, and picks the matching subsection below.

Prerequisites

  1. RunComfy CLI — npm i -g @runcomfy/cli
  2. RunComfy account — runcomfy login.
  3. CI / containers — set RUNCOMFY_TOKEN=<token>.
  4. A source video URL — formats and limits depend on the chosen route.

Route 1: Wan 2.7 Edit-Video — default for restyle / background / packaging

Model: wan-ai/wan-2-7/edit-video

Schema

FieldTypeRequiredDefaultNotes
promptstringyes—Lead with preservation. One edit direction per call.
videostringyes—MP4/MOV URL, 2–10s, ≤100MB.
reference_imagestringno—URL — use for direct design / appearance transfer only.
resolutionenumno(input)720p or 1080p.
aspect_ratioenumno(input)W:H. Defaults to input.
durationintno00 = match input; 2–10 = truncate from start.
audio_settingenumnoautoauto or origin (preserve source audio).
seedintno—Reproducibility.

Invoke

Background swap, identity preserved, audio kept:

bash
runcomfy run wan-ai/wan-2-7/edit-video \
  --input '{
    "prompt": "Preserve the speaker'\''s face, pose, and lip movement; change the background to a modern office with neutral lighting.",
    "video": "https://.../speaker.mp4",
    "audio_setting": "origin"
  }' \
  --output-dir <absolute/path>

Packaging swap with reference image:

bash
runcomfy run wan-ai/wan-2-7/edit-video \
  --input '{
    "prompt": "Maintain the original framing and hand movement; replace the packaging design using the reference image.",
    "video": "https://.../hand-holding-package.mp4",
    "reference_image": "https://.../new-packaging.png",
    "audio_setting": "origin"
  }' \
  --output-dir <absolute/path>

Prompting tips

  • Preservation goals first: "Preserve [face / pose / motion / framing / lip movement]; [then state the change]".
  • One edit direction per call. Compound edits drift on motion.
  • reference_image only when justified (packaging swap, costume swap with target visual). Don't pass refs for general restyle.
  • audio_setting: "origin" for talking-head where you don't want soundtrack regenerated.
  • Source video constraints: 2–10s, ≤100MB.

Route 2: Kling 2.6 Pro Motion Control — when motion FROM a reference clip is the point

Model: kling/kling-2-6/motion-control-pro

Use when the user wants to transfer the motion of a reference video onto a target character (driven by an image OR another video). This isn't restyle — it's motion mapping with identity hold.

Schema

FieldTypeRequiredNotes
promptstringyesDescribe target motion / style.
imagestringyes (image orientation)Reference for character / background consistency.
videostringyesMotion reference. 10–30s depending on orientation.
keep_original_soundboolnoPreserve audio from reference video.
character_orientationenumyesimage (max 10s output) or video (max 30s output).

Invoke

bash
runcomfy run kling/kling-2-6/motion-control-pro \
  --input '{
    "prompt": "A young american woman dancing",
    "image": "https://.../target-character.jpg",
    "video": "https://.../motion-reference-dance.mp4",
    "character_orientation": "image",
    "keep_original_sound": true
  }' \
  --output-dir <absolute/path>

Prompting tips

  • Subject must be > 5% of frame in the image reference for clean identity hold.
  • Spatial constraints help: "character on left side, background motion right".
  • Simplify if results drift between iterations — drop adjectives, keep core motion description.
  • character_orientation: "image" caps output at 10s; "video" allows 30s.

Route 3: Lucy Edit Restyle — lightweight identity-stable restyle / outfit swap

Model: decart/lucy-edit/restyle

Use when the edit is localized style modification — outfit swap, scene relight, atmospheric restyle — and identity preservation is critical. Lighter-weight than Wan 2.7 Edit; capped at 720p.

Schema

FieldTypeRequiredDefaultNotes
promptstringyes—Natural-language edit instruction.
video_urlstringyes—MP4/MOV/WEBM/GIF.
resolutionenumno720p720p only on this tier.

Invoke

Outfit swap:

bash
runcomfy run decart/lucy-edit/restyle \
  --input '{
    "prompt": "Change outfit to professional business attire; preserve face and motion.",
    "video_url": "https://.../subject-walking.mp4"
  }' \
  --output-dir <absolute/path>

Atmospheric restyle:

bash
runcomfy run decart/lucy-edit/restyle \
  --input '{
    "prompt": "Make lighting warm and golden hour; preserve face, pose, and motion.",
    "video_url": "https://.../subject-portrait.mp4"
  }' \
  --output-dir <absolute/path>

Prompting tips

  • Localized change phrasing wins. "Outfit", "lighting", "background" — pick one bucket.
  • Preserve identity goals — "preserve face and motion" is enough; don't over-specify.
  • Avoid total replacement ("astronaut in space" works; "swap subject for a different person" doesn't). Lucy is built for localized style mods, not full character swap.
  • No aspect ratio control — output matches input. Cropping happens server-side if you don't pre-match.

Limitations

  • Each route inherits its model's limits. Wan 2.7 Edit: 2–10s, 1080p ceiling. Kling: 10s (image orientation) or 30s (video orientation). Lucy: 720p ceiling, no aspect control.
  • No multi-route blending. This skill picks one model per call.
  • Brand-specific overrides — if the user named a specific model, route to the corresponding brand skill (wan-2-7) for fuller treatment.

Exit codes

codemeaning
0success
64bad CLI args
65bad input JSON / schema mismatch
69upstream 5xx
75retryable: timeout / 429
77not signed in or token rejected

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The skill picks one of Wan 2.7 Edit-Video / Kling 2.6 Pro Motion Control / Lucy Edit Restyle based on user intent and invokes runcomfy run <model_id> with the matching JSON body. The CLI POSTs to the Model API, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.

Security & Privacy

  • Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers.
  • Input boundary: the user prompt is passed as a JSON string to the CLI via --input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content.
  • Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
  • Outbound endpoints: only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks.
  • Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.

Frequently asked questions

What does the Video Edit AI skill do?

Edit existing video on RunComfy — this skill is a smart router that matches the user's intent to the right edit model in the RunComfy catalog. Picks Wan 2.7 Edit-Video (general restyle / background swap / packaging swap, identity + motion preservation), Kling 2.6 Pro Motion Control (transfer precise motion from a reference video to a target character), or Lucy Edit Restyle (lightweight identity-stable restyle / outfit swap). Bundles each model's documented prompting patterns so the skill gets sharper edits without burning iterations on the wrong model. Calls `runcomfy run <vendor>/<model>/<...

Why use Video Edit on TypingMind?

Because you install it once and use it with any model. Video Edit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Video Edit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/genmedia-labs/skills/tree/main/video-edit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Video Edit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Video Edit?

As many as you like. As long as a model supports skills, you can use Video Edit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Video Edit AI skill free?

Yes. It is published on GitHub by genmedia-labs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇