scenario-vidu — Claude Code skill: what it does, how to install
Directs video generation with Vidu models on Scenario using MCP. It structures text-to-video, keyframe bridging, and multi-reference identity workflows.
npx skills add scenario-labs/skills --skill scenario-vidu -a claude-codeWhat scenario-vidu does
Shengshu Technology's Vidu lineup on Scenario uses separate model identifiers for each mode and tier. Modes like T2V, I2V, and Reference2V are split across Q3, Q2, Q1, and 2.0 releases. This skill guides the agent to discover model IDs via search and treat model_schema_get as the definitive contract. Always inspect the schema first. In I2V mode, bridging two frames demands exactly two asset IDs with generationType: "start_end_to_video", while aspectRatio is omitted because geometry follows the source images.
Durations differ across tiers. Q3 runs from 1 to 16 seconds. Q2 caps start and end interpolation at 8 seconds, with a maximum length of 10. The 2.0 I2V model accepts only 4 or 8 seconds, and 8 seconds requires 720p. The audio parameter only controls background music, and it silently turns off on longer Q2 clips.
Cost changes fast. Because duration and resolution scale job pricing several times over, running model_run with dry_run=true is necessary before launching batches. To handle asset uploads and track jobs with jobs_wait, install the companion scenario skill.
What it helps with
- select the exact Vidu model ID for T2V, I2V, or Reference2V
- interpolate motion between two uploaded keyframes
- preserve character appearance across up to 7 reference images
- verify duration and resolution bounds before running batches
Example prompts for the agent
- Find a Vidu I2V model and interpolate between two keyframes for 8 seconds
- Generate a clip preserving character appearance from three reference images using Vidu Reference2V
- Check the schema for Vidu Q2 Turbo and perform a dry run
How to install scenario-vidu
1Skills CLI (Vercel)
npx skills add scenario-labs/skills --skill scenario-vidu -a claude-code2Manually: put the files in place
~/.claude/skills/scenario-vidu/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/scenario-vidu/
1Skills CLI (Vercel)
npx skills add scenario-labs/skills --skill scenario-vidu -a codex2Manually: put the files in place
.agents/skills/scenario-vidu/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add scenario-labs/skills --skill scenario-vidu -a cursor2Manually: put the files in place
.cursor/skills/scenario-vidu/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install scenario-labs/skills scenario-vidu2Manually: put the files in place
.github/skills/scenario-vidu/SKILL.md1Skills CLI (Vercel)
npx skills add scenario-labs/skills --skill scenario-vidu -a gemini-cli2Platform CLI
gemini skills install https://github.com/scenario-labs/skills --path skills/scenario-viduManually: put the files in place
.devin/skills/scenario-vidu/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add scenario-labs/skills --skill scenario-vidu -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about scenario-vidu
How to install scenario-vidu in Claude Code?
Run npx skills add scenario-labs/skills --skill scenario-vidu -a claude-code. The skill writes to ~/.claude/skills/scenario-vidu/SKILL.md.
What does scenario-vidu do?
It instructs agents on calling Shengshu Technology's Vidu models on Scenario via MCP. It covers prompt formats, tier limits from Q1 to Q3, and parameter requirements.
Does a reference image fix the opening frame in Reference2V?
No, Reference2V uses images only to guide character identity, props, and palette. To start on an exact initial still, switch to an I2V model.
Source text
SKILL.md · MIT
---
name: scenario-vidu
description: "Use when generating video with Vidu models on Scenario via MCP: text-to-video, image-to-video from a single still, start and end frame interpolation, reference-to-video keeping characters and props consistent from up to 7 reference images or reference videos, anime-style motion, movement amplitude control, or deciding between Q3, Q2, Q1, and 2.0 tiers. Keywords: Vidu Q3 Pro, Q2 Turbo, Shengshu Technology, T2V, I2V, R2V, Reference2V, start end frame, background music toggle."
license: MIT
---
# Scenario Vidu Video
## Overview
Vidu, Shengshu Technology's video family on Scenario, ships one model per mode per tier instead of
folding every mode into one model: the model name carries both the mode (T2V, I2V, Reference2V) and
the tier (Q3, Q2, Q1, 2.0). Fifteen members were live at authoring time, so `search` the family,
pick by name, and treat `model_schema_get` as the contract, since caps disagree at every tier
boundary.
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
Choose the model line by what you hold (input names from the live schemas):
| You hold | Line | Key inputs |
| -------------------- | ----------- | --------------------------------------------------------- |
| Text only | T2V | `prompt`, `aspectRatio`, `duration`, `resolution` |
| One still to animate | I2V | `generationType: "image_to_video"`, `images` with one id |
| Start and end frames | I2V | `generationType: "start_end_to_video"`, `images` with two |
| Identity references | Reference2V | `images`, up to 7 |
In start/end mode array order decides: the first id opens the clip, the second closes it, and
`generationType` must match the image count. No I2V member exposes `aspectRatio`: geometry follows
the source stills. Reference2V carries identity (characters, props, palette), not the opening state;
to open on an exact frame, switch to an I2V member. One Reference2V member (Q2 Pro at authoring
time) also took `videos`: up to 2 reference videos (one of 8 seconds or two of 5, 100MB each, aspect
between 1:4 and 4:1), requiring `images` or `videos`.
Every member takes `seed`. `audio` (default false) is a background-music toggle, not sound design,
and on most Q2 members it silently does nothing at 9 or 10 seconds.
## Tier picks the caps
At authoring time: Q3 ran 1 to 16 seconds; Q2 ran 1 to 10, with start/end mode capped at 8; 2.0 I2V
took exactly 4 or 8 seconds, and 8 only at 720p; Q1 exposed no duration or resolution at all, and
2.0 Reference2V no duration. `movementAmplitude` (auto, small, medium, large) exists only on the Q1
and 2.0 lines, and the general or anime `style` selector only on Q1 I2V members; on Q2 and Q3,
motion energy and style go in the prompt. Turbo and Fast variants cut latency at the same duration
and resolution caps as their Pro siblings. `duration` and `resolution` both move cost, several-fold
on one member alone, so `dry_run` the exact job before a batch.
## Two prompt shapes
T2V and I2V want a 120 to 180 word single-shot paragraph in present tense: scene and lighting, one
or two motions, one camera move in plain verbs (pan, dolly, zoom in), emotion as physical cues ("her
shoulders slump"), no cuts, and in I2V nothing that is not already in the still. Reference2V wants
the opposite: one short sentence, roughly 20 to 40 words, naming which element comes from which
reference by position, "the character from image1 wearing the armor from image2, walking through a
snowstorm". Prompt length caps differ per member, 2000 to 5000 characters.
## Worked example: bridging two keyframes
1. `search` with `target="models"`, `query="vidu"`, `public=true`. Prefer the newest tier in the
mode you need, e.g. `model_vidu-i2v-q3-pro` (a live hit at authoring time: re-discover each
session).
2. `model_schema_get` with that id: duration bounds, resolutions, defaults.
3. `upload_asset` the start and end stills (see the `scenario` skill) for two asset ids.
4. `model_run` with that `model_id`, `dry_run=true`, and
`parameters={"generationType": "start_end_to_video", "images": ["asset_start", "asset_end"], "prompt": "The knight slowly lowers his sword as dusk settles over the courtyard. The camera dollies in on his face.", "duration": 8, "resolution": "1080p"}`;
expand the prompt to the full paragraph shape above in real runs, and re-estimate after any
change to duration or resolution.
5. Re-run `model_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`.
6. `asset_display` the output and check both anchor frames landed.
## Common mistakes
- Two images with `generationType: "image_to_video"`, or one with start/end: the type must match the
image count, and order sets start versus end.
- Expecting a Reference2V clip to open on a reference image: references fix identity, not frame one;
use an I2V member for exact opening frames.
- Carrying caps across tiers: 16 seconds is Q3 only; 2.0 I2V accepts only 4 or 8, and 8 forces 720p.
- Prompting dialogue or sound effects: `audio` only adds background music, and it drops out at 9 or
10 seconds on most Q2 members.
- A 150-word paragraph on Reference2V, or a bare sentence on T2V: the two modes want opposite prompt
shapes.
- Passing `videos` to any Reference2V member: at authoring time only one took reference videos; read
the schema first.
© scenario-labs · MIT · scenario-labs/skills