Agent skill

Scenario Kling

by scenario-labs in scenario-labs/skills

A skill your agent uses when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts…

MITAuto-check passedMedia & Creative

Install Scenario Kling

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-kling .claude/skills/scenario-kling && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .claude/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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

$skill-installer install https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling

Type 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.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/scenario-kling .agents/skills/scenario-kling && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .agents/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/scenario-kling .cursor/skills/scenario-kling && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .cursor/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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

$ gemini skills install https://github.com/scenario-labs/skills.git --path skills/scenario-kling

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/scenario-kling .gemini/skills/scenario-kling && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .gemini/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling

Installs 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).

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/scenario-kling .github/skills/scenario-kling && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .github/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-kling -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-kling --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/scenario-kling .opencode/skills/scenario-kling && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "scenario-kling" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-kling into .opencode/skills/scenario-kling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-kling", 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-kling
GitHub stars: 946
Token cost: ~1.9k tokens
SKILL.md length: 985 words
Files: 1
Skills in repo: 146
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts…

Works in 6 steps: search with target="models",… → model_schema_get with that id:… → upload_asset the start frame and the… → …
Editing video with Kling models on Scenario via MCP: text-to-video
SKILL.md covers Overview, Quick reference, Audio is a per-member switch and Motion control reads two inputs, plus 2 more sections
Calls npx

What it does

Scenario Kling is an agent skill from scenario-labs/skills. Use when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers. Keywords: Kling V3, O1, 2.6, Omni, Kuaishou, T2V, I2V, V2V.

Its SKILL.md is about 1.9k 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. 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 Kling models on Scenario via MCP: text-to-video
Image-to-video with first and last frames
Multi-shot sequences with per-shot prompts
Consistent characters via elements and reference images

Example prompts

“/scenario-kling”

Requirements

Node.js

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

search with target="models", query="kling image to video", public=true. Prefer the newest non-deprecated hit, e.g. model_kling-v3-i2v-pro…
model_schema_get with that id: multiPrompt shape, duration values, element caps.
upload_asset the start frame and the character's frontal photo (see the scenario skill).
model_run with that model_id, dry_run=true, and parameters={"startImage": "asset_s", "multiPrompt": [{"prompt": "Wide shot, @Element1…
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…
asset_display the output and review both shots with sound.

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 Kling loads about 1.9k tokens when it runs. Until then it costs about 127 tokens; SKILL.md has 985 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~127
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

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). 985 words, ~1,878 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-kling/SKILL.md (or your agent's skills folder).

name: scenario-kling
description: Use when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers. Keywords: Kling V3, O1, 2.6, Omni, Kuaishou, T2V, I2V, V2V.
license: MIT

Scenario Kling Video

Overview

Kling, Kuaishou's video family on Scenario, ships as specialists, eighteen at authoring time: V3 (Omni plus dedicated T2V and I2V tiers), O1, 2.6, motion control, lipsync, and a talking avatar. Pick the member whose conditioning matches the job, then treat model_schema_get as the contract: the same parameter changes shape, default, and legality between members. Kling Video to Audio is audio output, the scenario-audio skill's domain.

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 by job; discover ids with search (target="models", query="kling", public=true):

Job	Members
Every mode in one model, tier via `mode`	V3 Omni (`standard` 720p, `pro` 1080p, `4k`)
Text to video at a fixed tier	V3 T2V Standard / Pro / 4K, 2.6 T2V Pro
Animate a still, optional last frame	V3 I2V Standard / Pro / 4K, O1 I2V, 2.6 I2V Pro
Consistent characters from photos	O1 Reference Images, V3 I2V `elements`
Edit or restyle footage by prompt	O1 Video Editing / Reference Video, Omni (`videoReferenceType: "base"`)
Motion from a video onto a character image	Motion Control (V3 Pro / Std, V2.6)
Talking head	AI Avatar (image plus audio), Lipsync (video plus audio or text)

Schema traps (names from live schemas, caps at authoring time):

V3 dedicated lines take prompt or multiPrompt, never both; multiPrompt is an array of {prompt, duration} shots, and shotType (customize or intelligent) exists only on the V3 T2V members and I2V 4K. Omni keeps prompt required; its multiPrompt is a JSON string of up to 6 shots whose durations sum to duration.
duration is a string enum on most members ("5", not 5); Omni alone takes a number, 3 to 15. The V3 dedicated lines reach 15 seconds; O1 and 2.6 stop at 10.
On O1 and V3 I2V an element is a frontalImage plus up to 4 angle referenceImages: both required on O1, each optional on V3 I2V, where a video can define the element instead.
Budgets shrink beside a video: O1 Reference Images takes 7 total (elements plus images), the O1 video members 4, and Omni's referenceImages drops from 7 to 4 next to referenceVideo. Tags bind by order (@Element1, @Image1); Omni prompts use <<<image_1>>> and <<<video_1>>>.
A reference clip runs 3 to 10 seconds on Omni and the O1 video members, 2 to 10 on Lipsync (trim first, per scenario-video). Omni's referenceVideo defaults to videoReferenceType: "feature", lending style and camera to a new clip; "base" edits the clip and ignores duration; 4k mode refuses a reference video either way.
cfgScale (0 to 1, default 0.5): raise toward 0.8 for storyboard fidelity, drop toward 0.3 to let the model invent.
Prompt in director order: scene, subject, action, one camera move, then audio and style; natural sentences beat tag lists, and complex scenes hold together near 5 seconds, not 15.

Audio is a per-member switch

generateAudio defaults true on the V3 dedicated lines and 2.6 T2V, false on Omni and 2.6 I2V, and does not exist on O1 (editing members carry source audio via keepAudio). It is refused beside Omni's reference video and beside lastFrameImage on 2.6 I2V; the 4K members bill per second either way. Voice output is Chinese and English, other languages auto-translate to English: put dialogue in quotes in the prompt, lowercase for English speech, uppercase for acronyms. For new speech on existing footage use Lipsync: an audio file, or text with a voiceId, never both.

Show full SKILL.md (384 more words)Show less

Motion control reads two inputs

Motion members require a character image and a driving video; characterOrientation names which input holds the character and, on V2.6, caps the driving clip at authoring time: 10 seconds for image, 30 for video. Defaults differ (V3 Std says video, the others image), so set it explicitly. keepOriginalSound decides whether the source audio survives.

Worked example: two-shot character clip from a still

search with target="models", query="kling image to video", public=true. Prefer the newest non-deprecated hit, e.g. model_kling-v3-i2v-pro (a live hit at authoring time: re-discover each session).
model_schema_get with that id: multiPrompt shape, duration values, element caps.
upload_asset the start frame and the character's frontal photo (see the scenario skill).
model_run with that model_id, dry_run=true, and parameters={"startImage": "asset_s", "multiPrompt": [{"prompt": "Wide shot, @Element1 crosses the plaza, slow dolly-in", "duration": "5"}, {"prompt": "Close-up, @Element1 smiles and says: 'we made it'", "duration": "4"}], "generateAudio": true, "elements": [{"frontalImage": "asset_f"}]} for the cost estimate; re-estimate after changing durations, tier, or audio.
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.
asset_display the output and review both shots with sound.

Common mistakes

Passing both prompt and multiPrompt to a V3 dedicated line: exclusive there (Omni alone keeps prompt required).
Numeric durations: outside Omni, duration is the string "5", not 5.
Expecting audio beside a last frame (2.6 I2V) or a reference video (Omni): exclusive pairs.
Carrying one member's caps to another: 15 seconds, elements, and 4K each exist on one member, not the next.
Compound camera moves ("dolly in while orbiting"): one dominant move per shot; split the rest across multiPrompt shots.
Overloaded negative prompts: a short artifact list steers; a long one stiffens motion.
Prompting Omni base to extend a clip: it edits in place, and no Kling member extends at authoring time. Continue from the clip's lastFrame id (asset_get) as the start frame of a new I2V run, then concatenate, per scenario-video.
Skipping dry_run on 4K or avatar runs: at authoring time 4K ran several times Standard and avatar cost spanned a 100x range. Iterate on a Standard tier; no V3, O1, or 2.6 schema carries a seed, so a 4K re-run of the keeper is a new take, while upscaling it (scenario-video) keeps the take.

Files

Just SKILL.md in skills/scenario-kling of scenario-labs/skills.

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Kling 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.

Scenario Kling compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Scenario Kling this skillscenario-labs/skills	946	—	~1.9k	Automated safety check: Pass	MIT	yesterday
Clipmivo VideoBarneyD66/clipmivo-tools	142	—	~945	Automated safety check: Pass	MIT	25 days ago
ComfyUI Local DriverSlavaSexton/ComfyUI-Agent-Kit	105	—	~12k	Automated safety check: Pass	Apache-2.0	1 mo ago
Generate VideoArcReel/ArcReel	5.4k	—	~1.3k	Automated safety check: Warn	AGPL-3.0	yesterday
Generate StoryboardArcReel/ArcReel	5.4k	—	~816	Automated safety check: Pass	AGPL-3.0	yesterday
Manage ProjectArcReel/ArcReel	5.4k	—	~1.6k	Automated safety check: Pass	AGPL-3.0	yesterday

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Works with

Model Context Protocol

Questions about Scenario Kling

What does Scenario Kling do?

A skill your agent uses when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts…. Scenario Kling is an agent skill from scenario-labs/skills. Use when generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers.

When should I use Scenario Kling?

Scenario Kling fits situations like: editing video with Kling models on Scenario via MCP: text-to-video; image-to-video with first and last frames; multi-shot sequences with per-shot prompts; consistent characters via elements and reference images.

How do I install Scenario Kling in Claude Code?

Run `npx skills add scenario-labs/skills --skill scenario-kling -a claude-code`. Or copy the skill folder (skills/scenario-kling in scenario-labs/skills) into .claude/skills/scenario-kling in your project. Claude Code loads it when a task matches its description.

How do I install Scenario Kling in Codex?

Run `npx skills add scenario-labs/skills --skill scenario-kling -a codex`. Or copy the skill folder (skills/scenario-kling in scenario-labs/skills) into .agents/skills/scenario-kling in your project. Codex loads it when a task matches its description.

Can I use Scenario Kling 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-kling -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-kling, .gemini/skills/scenario-kling, .github/skills/scenario-kling and .opencode/skills/scenario-kling in your project.

What does Scenario Kling need to run?

Going by SKILL.md and its folder, Scenario Kling needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Scenario Kling 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 Kling 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 Kling use?

Scenario Kling 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 Kling use?

About 1.9k tokens (SKILL.md is roughly 7.5k 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 Kling?

Skills that share tags, products or a category with Scenario Kling: Clipmivo Video (BarneyD66/clipmivo-tools, 142 stars), ComfyUI Local Driver (SlavaSexton/ComfyUI-Agent-Kit, 105 stars), Generate Video (ArcReel/ArcReel, 5.4k stars) and Generate Storyboard (ArcReel/ArcReel, 5.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Kling?

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.

Install Scenario Kling

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Scenario Kling Video

Overview

Quick reference

Audio is a per-member switch

Motion control reads two inputs

Worked example: two-shot character clip from a still

Common mistakes

Files

Compare with similar skills

Similar skills

More from scenario-labs/skills

Related

Questions about Scenario Kling