Edit Video
ArcReel/ArcReel
在剪辑时间线上剪辑一集，并按要求出成片或导出剪映草稿。本集视频已齐、要剪一版时使用；用户按片段编号提出修改（如「c3 太拖」），或要求配 BGM、出成片、导出剪映草稿、复制或重命名剪辑时间线、回到旧修订时，也使用本 skill。
A skill your agent uses when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip…
Install Scenario Wan
$ npx skills add scenario-labs/skills --skill scenario-wan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install scenario-labs/skills scenario-wan --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-wan .claude/skills/scenario-wan && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .claude/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/scenario-labs/skills/tree/main/skills/scenario-wanType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add scenario-labs/skills --skill scenario-wan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install scenario-labs/skills scenario-wan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/scenario-wan .agents/skills/scenario-wan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .agents/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-wan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install scenario-labs/skills scenario-wan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/scenario-wan .cursor/skills/scenario-wan && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .cursor/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/scenario-labs/skills.git --path skills/scenario-wan--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add scenario-labs/skills --skill scenario-wan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install scenario-labs/skills scenario-wan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/scenario-wan .gemini/skills/scenario-wan && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .gemini/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install scenario-labs/skills scenario-wanInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add scenario-labs/skills --skill scenario-wan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/scenario-wan .github/skills/scenario-wan && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .github/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add scenario-labs/skills --skill scenario-wan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install scenario-labs/skills scenario-wan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/scenario-wan .opencode/skills/scenario-wan && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "scenario-wan" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-wan into .opencode/skills/scenario-wan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-wan", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
scenario-wan- GitHub stars
- 946
- Token cost
- ~1.6k tokens
- SKILL.md length
- 813 words
- Files
- 1
- Skills in repo
- 146
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip…
- Works in 6 steps: search with target="models", query="wan… → model_schema_get with that id:… → upload_asset the opening and closing… → …
- Editing video with Wan models on Scenario via MCP: text-to-video
- SKILL.md covers Overview, Quick reference, Prompt the member's job and Where the audio comes from, plus 2 more sections
- Calls npx
What it does
Scenario Wan is an agent skill from scenario-labs/skills. Use when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip, instruction-based video editing, character motion transfer or person replacement (Animate), aspect ratio reframing, video outpainting, uploaded-audio sync or auto-generated audio, or multi-shot prompts with timing brackets. Keywords: Wan 2.7, 2.6, 2.5, 2.2, Alibaba, VACE, T2V, I2V, V2V, lip-sync, multiShots.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Media & Creative, covering AI video generation and Video production. It works with Model Context Protocol. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.
When your agent uses it
- Editing video with Wan models on Scenario via MCP: text-to-video
- Image-to-video from a still
- First and last frame brackets
- Extending a clip
Example prompts
- “/scenario-wan”
Requirements
- Node.js
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- search with target="models", query="wan image to video", public=true. Prefer the newest non-deprecated hit, e.g. model_wan-2-7-i2v (a live…
- model_schema_get with that id: exclusivity notes, caps, defaults.
- upload_asset the opening and closing stills (see the scenario skill) for asset ids.
- model_run with that model_id, dry_run=true, and parameters={"prompt": "She turns from the window and walks toward the door, coat swaying…
- Re-run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout, never a second model_run.
- asset_display the output and review motion and audio together.
What it can do on your machine
Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
npx
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Scenario Wan loads about 1.6k tokens when it runs. Until then it costs about 122 tokens; SKILL.md has 813 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 813 words, ~1,649 tokens.
Download SKILL.mdSave it as
.claude/skills/scenario-wan/SKILL.md (or your agent's skills folder).- name
- scenario-wan
- description
- Use when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip, instruction-based video editing, character motion transfer or person replacement (Animate), aspect ratio reframing, video outpainting, uploaded-audio sync or auto-generated audio, or multi-shot prompts with timing brackets. Keywords: Wan 2.7, 2.6, 2.5, 2.2, Alibaba, VACE, T2V, I2V, V2V, lip-sync, multiShots.
- license
- MIT
Scenario Wan Video
Overview
Wan, Alibaba's video family on Scenario, ships each job as its own member, and members a generation apart disagree on parameter names, not just numbers: pick the member with search, then treat model_schema_get as the contract before every run. Wan 2.7 Image is an image model, covered by the scenario-image skill.
Connection and the core loop: see the scenario skill in this repo; model-agnostic video work: the scenario-video skill. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.
Quick reference
Members by job (at authoring time):
| Job | Member | Required inputs |
|---|---|---|
| Text to video | 2.7, 2.6, 2.5 T2V | prompt |
| Animate a still | 2.7, 2.6, 2.5 I2V | image + motion prompt |
| Extend a clip | 2.7 I2V | video + prompt (excludes image) |
| Restyle footage | 2.7 Video Edit | video + edit prompt |
| Character performs a video's motion | 2.2 Animate (Move) | imageUrl + videoUrl |
| Swap the person in footage | 2.2 Animate (Replace) | videoUrl + imageUrl |
| Change aspect ratio | 2.2 Reframe | videoUrl |
| Expand the canvas | 2.2 Outpainting | videoUrl + prompt |
Parameters do not port across generations. At authoring time: the 2.7 generators take resolution (720p or 1080p) and whole-second duration from 2 to 15, with aspectRatio (16:9 through 3:4) on T2V only. 2.6 and 2.5 T2V instead take one size string such as "1920*1080", with duration from a fixed grid (5, 10, or 15 on 2.6; 5 or 10 on 2.5), while their I2V members take resolution. Video Edit takes a 2 to 10 second source; its duration is optional and truncates. Reframe and Outpainting have no duration: length is numFrames (81 to 241) at framesPerSecond (5 to 30), and output matches the source only when matchInputNumFrames and matchInputFramesPerSecond are true (both default false). Outpainting guides new content with up to 10 refImageUrls.
On 2.7 I2V, image and video are mutually exclusive, and endImage (last frame) is only valid alongside image. Resolution and duration carry cost (1080p ran about triple 720p on 2.7 T2V at authoring time), so dry_run before batches.
Prompt the member's job
T2V wants a full scene in natural language: subject action, one camera move, lighting, style tags. I2V wants motion only: the still already fixes look and composition, so re-describing it wastes the prompt. Video Edit wants instructions, one clear change per sentence with a precise target, plus preservation language ("keep subject identity and camera path"); referenceImage carries a target look. In-frame readable text is unreliable on every member; push artifacts into negativePrompt (Video Edit and Animate lack it).
2.6 alone does multi-shot: with multiShots true (the default, but active only while enablePromptExpansion is true), open with a global style line, then Shot 1 [0-3s] ..., Shot 2 [3-7s] ..., keeping characters and location continuous. enablePromptExpansion defaults true on the generators (helps thin prompts, adds latency) and false on Reframe and Outpainting.
Show full SKILL.md (333 more words)Show less
Where the audio comes from
The 2.7 generators always deliver audio: upload an audio file to drive it, or omit it and a synced track is generated from whatever sound the prompt describes, so prompt the ambience you want. On 2.6 and 2.5, audio comes only from an uploaded file (3 to 30 seconds, 15 MB or less at authoring time), which 2.6 lip-syncs. Video Edit's audioSetting decides the track: origin keeps the source audio, auto lets the model regenerate it. Animate carries the source track while mergeAudio stays true (the default).
Worked example: bracket a shot between two stills
searchwithtarget="models",query="wan image to video",public=true. Prefer the newest non-deprecated hit, e.g.model_wan-2-7-i2v(a live hit at authoring time: re-discover each session).model_schema_getwith that id: exclusivity notes, caps, defaults.upload_assetthe opening and closing stills (see thescenarioskill) for asset ids.model_runwith thatmodel_id,dry_run=true, andparameters={"prompt": "She turns from the window and walks toward the door, coat swaying; slow push-in. Room tone and distant traffic.", "image": "asset_open", "endImage": "asset_close", "duration": 5, "resolution": "1080p"}for the cost estimate; re-estimate after changing duration or resolution.- Re-run with
wait=false, thenjobs_waitwith the returned job id, re-called withpending_job_idson timeout, never a secondmodel_run. asset_displaythe output and review motion and audio together.
Common mistakes
- Combining
imagewithvideoon 2.7 I2V, or passingendImagewithoutimage: the schema forbids both. - Porting a 2.7 payload to 2.6 or 2.5 T2V: they take
size("1280*720"style), notresolutionplusaspectRatio, and off-grid durations fail. - Expecting Reframe or Outpainting to preserve length: defaults render 81 frames at 16 fps; set the two match flags.
- Outpainting's expand flags default to all four sides: set the unwanted directions (
expandTop,expandBottom,expandLeft,expandRight) to false. - Writing shot brackets with
enablePromptExpansionfalse:multiShotsis inert without it; no other member reads brackets. - Re-describing the still or requesting content changes in an I2V prompt: I2V animates; Video Edit changes content.
© scenario-labs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/scenario-wan of scenario-labs/skills.
Open the folder on GitHubat commit f6f8ab7
Compare with similar skills
Scenario Wan next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Scenario Wan this skillscenario-labs/skills | 946 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Edit VideoArcReel/ArcReel | 5.4k | — | ~1.6k | Automated safety check: Pass | AGPL-3.0 | |
| Avatar Videocalesthio/OpenMontage | 66k | — | ~1.6k | Automated safety check: Pass | AGPL-3.0 | |
| Cassette Video EditCassette-Editor/oh-my-cassette | 119 | 1 repos | ~3.4k | Automated safety check: Pass | MIT | |
| Beatdesign WorkspaceBeatAPI/BeatDesign | 140 | 1 repos | ~632 | Automated safety check: Pass | Apache-2.0 | |
| Blender MCP Videomicky-li-hd/VideoCoCo | 118 | — | ~1.1k | Automated safety check: Pass | None |
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Questions about Scenario Wan
What does Scenario Wan do?
A skill your agent uses when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip…. Scenario Wan is an agent skill from scenario-labs/skills. Use when generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip, instruction-based video editing, character motion transfer or person replacement (Animate), aspect ratio reframing, video outpainting, uploaded-audio sync or auto-generated audio, or multi-shot prompts with timing brackets.
When should I use Scenario Wan?
Scenario Wan fits situations like: editing video with Wan models on Scenario via MCP: text-to-video; image-to-video from a still; first and last frame brackets; extending a clip.
How do I install Scenario Wan in Claude Code?
Run `npx skills add scenario-labs/skills --skill scenario-wan -a claude-code`. Or copy the skill folder (skills/scenario-wan in scenario-labs/skills) into .claude/skills/scenario-wan in your project. Claude Code loads it when a task matches its description.
How do I install Scenario Wan in Codex?
Run `npx skills add scenario-labs/skills --skill scenario-wan -a codex`. Or copy the skill folder (skills/scenario-wan in scenario-labs/skills) into .agents/skills/scenario-wan in your project. Codex loads it when a task matches its description.
Can I use Scenario Wan in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scenario-labs/skills --skill scenario-wan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-wan, .gemini/skills/scenario-wan, .github/skills/scenario-wan and .opencode/skills/scenario-wan in your project.
What does Scenario Wan need to run?
Going by SKILL.md and its folder, Scenario Wan needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
Does Scenario Wan access the network?
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Scenario Wan safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Scenario Wan use?
Scenario Wan is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Scenario Wan use?
About 1.6k tokens (SKILL.md is roughly 6.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Scenario Wan?
Skills that share tags, products or a category with Scenario Wan: Edit Video (ArcReel/ArcReel, 5.4k stars), Avatar Video (calesthio/OpenMontage, 66k stars), Cassette Video Edit (Cassette-Editor/oh-my-cassette, 119 stars) and Beatdesign Workspace (BeatAPI/BeatDesign, 140 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Scenario Wan?
scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.
Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.