Scenario Grok Imagine Video logo

Scenario Grok Imagine Video

Organization
scenario-labs
scenario-grok-imagine-video

Use when generating or editing video with Grok Imagine models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video with @image tags for consistent people, products, or clothing, prompt-based editing, extending a clip from its last frame, native audio with lip-synced dialogue and sound effects, or choosing between first-frame and reference conditioning. Keywords: Grok Imagine Video 1.5, R2V, Grok Edit Video, Grok Extend Video, xAI, T2V, I2V, V2V.

Overview

Publisherscenario-labs
Repositoryskills
Skill namescenario-grok-imagine-video
Stars
970
Forks
114
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 scenario-labs on GitHub. Read the source before you install it.

Installation

Install the Scenario Grok Imagine Video 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/scenario-labs/skills/tree/main/skills/scenario-grok-imagine-video
  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/scenario-labs/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/scenario-grok-imagine-video .claude/skills/scenario-grok-imagine-video
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scenario Grok Imagine Video 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 Scenario Grok Imagine Video 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 Scenario Grok Imagine Video 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.

Scenario Grok Imagine Video

Overview

Grok Imagine, xAI's video family on Scenario, splits its modes across single-purpose members: text and first-frame generation, reference-to-video, prompt editing, and clip extension each live in their own model, so picking the member is picking the mode. Discover them with search and treat model_schema_get as the contract: members agree on prompt style and disagree on every cap. The Grok Imagine image models belong to the scenario-grok-imagine-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

Pick the member by intent (input names from the live schema):

IntentMemberInputs
Text-to-videoVideo 1.5prompt alone; aspectRatio auto lands on 16:9
Animate a stillVideo 1.5image + prompt; auto follows the image ratio
Identity, opening freeVideo 1.5 R2VreferenceImages + prompt tagging @image1
Restyle or swap in placeEdit Videovideo + a prompt naming only the changes
Continue a clipExtend Videovideo + a continuation prompt; duration is new seconds

Caps are per member, so read them off model_schema_get. At authoring time the generation members took 1 to 15 seconds, 1 to 4 numOutputs, and eight aspectRatio values including auto; 1080p existed only on Video 1.5's text and first-frame modes, while R2V stopped at 720p and defaulted to 480p. The earlier unversioned Grok Imagine Video takes the same inputs as Video 1.5, also caps at 720p, and runs cheaper per dry_run. R2V took up to 7 referenceImages; Extend generated 2 to 10 new seconds; Edit exposed no duration or resolution and preprocessed its source down to 8.7 seconds at 720p, so trim to the segment first (see scenario-video). No seed, negative prompt, or camera parameter exists anywhere in the family.

First frame or references

image locks frame one: the video opens on that exact composition and animates out of it. referenceImages (its own member, R2V) carries people, products, and clothing across the shot without deciding how it opens. Tags bind by array order: @image1 is referenceImages[0] (<IMAGE_1> also works), and one clean subject per reference keeps control; a busy reference dilutes it. If the opening must match a composition exactly, render that still and pass it as image; when only a face, product, or outfit must stay consistent, use R2V and tag each reference where it acts.

Sound is prompted, not switched

Generation members produce native audio and no parameter controls it: the prompt is the whole mixing desk. Left unaddressed, the track tends toward generic background music, so end every prompt with named sounds ("Audio: rain on glass, distant traffic") or "no music". Dialogue written in quotes with a delivery verb lip-syncs: She says calmly: "We're live." Structure the rest like a director: scene, camera, style, motion, audio, in present tense, one continuous shot, one dominant camera move, physical actions instead of named emotions. 80 to 150 words touching at least three of those layers beat a one-line scene; editing prompts run shorter, naming only what changes. Extension prompts describe the next beat, not a new scene: open with a bridge ("the shot continues"), keep the established light and cast, and restate the audio.

Worked example: dialogue over an animated hero still

  1. search with target="models", query="grok imagine video", public=true. Match the member by name: first-frame animation wants e.g. model_xai-grok-imagine-video-1-5 (a live hit at authoring time: re-discover each session).
  2. model_schema_get with that id: fields, caps, and defaults before anything else.
  3. upload_asset the hero still (see the scenario skill) to get its asset id.
  4. model_run with that model_id, dry_run=true, and the exact parameters={"prompt": "The frame shows a knight on a cliff at dusk. She lowers her sword, turns to the camera, and says quietly: 'It ends tonight.' Slow dolly-in, wind lifting her cloak. Audio: wind, distant thunder, her line clear. No music.", "image": "asset_abc", "duration": 8, "resolution": "1080p"} for the cost estimate; re-estimate after any change to duration, resolution, or numOutputs.
  5. Repeat 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 watch it with sound: the audio direction is judged by ear.

Common mistakes

  • Leaving audio to the default: generic music appears; direct the sound or state "no music" in every prompt.
  • Prompting an exact opening frame in R2V: references guide identity, not frame one; pass the still as image on Video 1.5.
  • Expecting 1080p everywhere: at authoring time it existed only on Video 1.5 text and first-frame runs, and R2V silently defaults to 480p.
  • Feeding Edit Video a long clip and expecting full-length output: the source is preprocessed down (8.7 seconds at authoring time); trim to the segment first.
  • Reading Extend's duration as total length: it counts only new footage.
  • Stacking camera moves or contradictory directions ("zoom in as the camera pulls back"): one dominant move per shot.

Frequently asked questions

What does the Scenario Grok Imagine Video AI skill do?

Use when generating or editing video with Grok Imagine models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video with @image tags for consistent people, products, or clothing, prompt-based editing, extending a clip from its last frame, native audio with lip-synced dialogue and sound effects, or choosing between first-frame and reference conditioning. Keywords: Grok Imagine Video 1.5, R2V, Grok Edit Video, Grok Extend Video, xAI, T2V, I2V, V2V.

Why use Scenario Grok Imagine Video on TypingMind?

Because you install it once and use it with any model. Scenario Grok Imagine Video 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 Scenario Grok Imagine Video in TypingMind?

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

Which AI models can use Scenario Grok Imagine Video?

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 Scenario Grok Imagine Video?

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

Is the Scenario Grok Imagine Video AI skill free?

Yes. It is published on GitHub by scenario-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.

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