Agent skill

Aliyun Kling Video

A skill your agent uses when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation).

MITAuto-check passedMedia & Creative

Install Aliyun Kling Video

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-kling-video -a claude-code

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-kling-video --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/cinience/alicloud-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .claude/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .claude/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video

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 cinience/alicloud-skills --skill aliyun-kling-video -a codex

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-kling-video --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .agents/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .agents/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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 cinience/alicloud-skills --skill aliyun-kling-video -a cursor

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-kling-video --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .cursor/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .cursor/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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/cinience/alicloud-skills.git --path skills/ai/video/aliyun-kling-video

--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 cinience/alicloud-skills --skill aliyun-kling-video -a gemini-cli

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-kling-video --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/cinience/alicloud-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .gemini/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .gemini/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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 cinience/alicloud-skills aliyun-kling-video

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 cinience/alicloud-skills --skill aliyun-kling-video -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .github/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .github/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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 cinience/alicloud-skills --skill aliyun-kling-video -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 cinience/alicloud-skills aliyun-kling-video --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/cinience/alicloud-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai/video/aliyun-kling-video .opencode/skills/aliyun-kling-video && 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 "aliyun-kling-video" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-kling-video into .opencode/skills/aliyun-kling-video/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-kling-video", 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: aliyun-kling-video
GitHub stars: 397
Token cost: ~2.2k tokens
SKILL.md length: 632 words
Files: 4 (incl. scripts, references)
Skills in repo: 96
Repo updated: Aug 11, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

A skill your agent uses when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation).

Works in 5 steps: Confirm user intent: t2v, i2v,… → Select appropriate model (standard for… → Prepare media array with correct types… → …
Generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation
SKILL.md covers Validation, Output And Evidence, Prerequisites and Critical model names, plus 10 more sections
Runs Python scripts from its folder; calls python and python3; reaches dashscope.aliyuncs.com; needs DASHSCOPE_API_KEY and API_KEY

What it does

Aliyun Kling Video is an agent skill from cinience/alicloud-skills. Use when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation). Use when implementing text-to-video, image-to-video, reference-to-video, smart storyboard, or video editing via the video-synthesis async API.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api_reference.md`, `references/sources.md` and `scripts/generate_kling_video.py`).

It sits in Media & Creative, covering AI video generation. It works with Alibaba Cloud. The repository describes itself as: alibaba cloud skills，qwen ，wan and all skills. The licence is MIT.

When your agent uses it

Generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation
Kling/kling-v3-omni-video-generation)
Implementing text-to-video
Reference-to-video

Example prompts

“/aliyun-kling-video”

Requirements

Python 3
A credential in DASHSCOPE_API_KEY
A credential in API_KEY

Workflow steps

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

Confirm user intent: t2v, i2v, reference-to-video, editing, or storyboard.
Select appropriate model (standard for basic t2v/i2v, omni for reference/editing).
Prepare media array with correct types and valid URLs.
Create async task and poll for results.
Download and save generated video before URL expiration.

What it can do on your machine

Read from SKILL.md and the folder at commit 1818263. 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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- dashscope.aliyuncs.com
Also links to:
- bailian.console.aliyun.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- DASHSCOPE_API_KEY
- API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Aliyun Kling Video loads about 2.2k tokens when it runs, and up to ~3.4k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 632 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~74
When it runs · the whole SKILL.md, loaded when a task matches: ~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3.4k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from cinience/alicloud-skills at commit 1818263, republished under its MIT licence (© cinience). 632 words, ~2,200 tokens.

Download SKILL.mdSave it as .claude/skills/aliyun-kling-video/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: aliyun-kling-video
description: Use when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation). Use when implementing text-to-video, image-to-video, reference-to-video, smart storyboard, or video editing via the video-synthesis async API.

Kling V3 Video Generation

Validation

bash

mkdir -p output/aliyun-kling-video
python -m py_compile skills/ai/video/aliyun-kling-video/scripts/generate_kling_video.py && echo "py_compile_ok" > output/aliyun-kling-video/validate.txt

Pass criteria: command exits 0 and output/aliyun-kling-video/validate.txt is generated.

Output And Evidence

Save task IDs, polling responses, and final video URLs to output/aliyun-kling-video/.
Keep at least one end-to-end run log for troubleshooting.

Prerequisites

Install dependencies (recommended in a venv):

bash

python3 -m venv .venv
. .venv/bin/activate
python -m pip install requests

Set DASHSCOPE_API_KEY in your environment (must be Beijing region API Key).
Enable Kling in 百炼控制台 — search "kling" and activate.

Critical model names

kling/kling-v3-video-generation — standard model: t2v, i2v (first frame, first+last frame)
kling/kling-v3-omni-video-generation — omni model: adds reference-to-video, video editing, multi-subject references

Capabilities

Capability	Model	Required media
Text-to-video	both	none
Smart storyboard (multi-shot)	both	none (use `multi_prompt`)
Image-to-video (first frame)	both	`first_frame`
Image-to-video (first+last frame)	both	`first_frame` + `last_frame`
Reference-to-video	omni only	`refer` and/or `feature`
Video editing	omni only	`base` + optional `refer`

API endpoint (async only)

POST https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis

Required headers:

Authorization: Bearer $DASHSCOPE_API_KEY
Content-Type: application/json
X-DashScope-Async: enable

Region: Beijing only. No Singapore endpoint.

Normalized interface

Request (input)

prompt (string, conditional) — up to 2500 characters. Required for shot_type=intelligence. For omni reference-to-video, use <<<element_1>>>, <<<image_1>>>, <<<video_1>>> to reference media.
negative_prompt (string, optional) — content to exclude
media (array, optional) — media objects with type and url:
- Standard model types: first_frame, last_frame
- Omni model types: first_frame, last_frame, refer, base, feature
multi_shot (boolean, optional) — enable multi-shot generation (default: false)
shot_type (string, conditional) — intelligence (AI auto-split) or customize (manual). Required when multi_shot=true.
multi_prompt (array, optional) — per-shot prompts when shot_type=customize
element_list (array, optional) — multi-subject element images (omni model only)
keep_original_sound (string, optional) — no (default) or yes, for videos (omni model only)

Request (parameters)

mode (string, optional) — pro (default, 1080P) or std (720P)
aspect_ratio (string, conditional) — 16:9 (default), 9:16, 1:1. Required for t2v and reference-to-video.
duration (integer, optional) — video length [3, 15] seconds (default: 5). When using reference video, [3, 10].
audio (boolean, optional) — generate audio (default: false). Affects pricing.
watermark (boolean, optional) — add "可灵 AI" watermark (default: false)

Media input limits

Images (first_frame, last_frame, refer):

Formats: JPEG, JPG, PNG (no transparency)
Resolution: [300, 8000] pixels per side
Max size: 10MB

Videos (base, feature):

Formats: mp4, mov
Duration: 3-10s
Resolution: [720, 2160] pixels per side
Frame rate: 24-60 fps
Max size: 200MB

Media combination rules

kling/kling-v3-video-generation:

i2v first frame: first_frame (1 image)
i2v first+last: first_frame + last_frame (1 each)

kling/kling-v3-omni-video-generation (all above plus):

Reference: feature only (1 video), or refer only (up to 7 with elements), or feature+refer (1 video + up to 4 with elements), or feature+first_frame (1 video + 1 image)
Video editing: base only (1 video), or base+refer (1 video + up to 4 with elements)

Show full SKILL.md (227 more words)Show less

Response (task creation)

output.task_id (string) — valid 24 hours
output.task_status (string) — PENDING | RUNNING | SUCCEEDED | FAILED | CANCELED
request_id (string)

Response (task result)

output.video_url (string) — generated video URL
output.watermark_video_url (string) — watermarked video URL
usage.duration (integer), usage.size (string), usage.fps (integer), usage.audio (boolean)

Quick start (Python + HTTP)

python

import os
import json
import time
import requests

API_KEY = os.getenv("DASHSCOPE_API_KEY")
BASE_URL = "https://dashscope.aliyuncs.com/api/v1"

def create_kling_task(req: dict) -> str:
    """Create a Kling video generation task and return task_id."""
    payload = {
        "model": req.get("model", "kling/kling-v3-video-generation"),
        "input": {"prompt": req.get("prompt", "")},
        "parameters": {
            "mode": req.get("mode", "pro"),
            "duration": req.get("duration", 5),
            "audio": req.get("audio", False),
            "watermark": req.get("watermark", False),
        },
    }
    if req.get("aspect_ratio"):
        payload["parameters"]["aspect_ratio"] = req["aspect_ratio"]
    if req.get("negative_prompt"):
        payload["input"]["negative_prompt"] = req["negative_prompt"]
    if req.get("media"):
        payload["input"]["media"] = req["media"]

    resp = requests.post(
        f"{BASE_URL}/services/aigc/video-generation/video-synthesis",
        headers={
            "Authorization": f"Bearer {API_KEY}",
            "Content-Type": "application/json",
            "X-DashScope-Async": "enable",
        },
        json=payload,
    )
    resp.raise_for_status()
    data = resp.json()
    return data["output"]["task_id"]


def poll_task(task_id: str, interval: int = 15) -> dict:
    """Poll until task completes. Returns final response."""
    while True:
        resp = requests.get(
            f"{BASE_URL}/tasks/{task_id}",
            headers={"Authorization": f"Bearer {API_KEY}"},
        )
        resp.raise_for_status()
        data = resp.json()
        status = data["output"]["task_status"]
        if status in ("SUCCEEDED", "FAILED", "CANCELED"):
            return data
        time.sleep(interval)

Usage examples

python

# Text-to-video
task_id = create_kling_task({
    "prompt": "一只小猫在月光下奔跑",
    "aspect_ratio": "16:9",
    "duration": 5,
    "mode": "std",
})

# Image-to-video (first frame)
task_id = create_kling_task({
    "prompt": "花朵绽放的延时摄影",
    "media": [{"type": "first_frame", "url": "https://example.com/flower.jpg"}],
    "duration": 5,
})

# Reference-to-video with omni model
task_id = create_kling_task({
    "model": "kling/kling-v3-omni-video-generation",
    "prompt": "一只<<<element_1>>>在月光下奔跑",
    "media": [{"type": "refer", "url": "https://example.com/cat.jpg"}],
    "aspect_ratio": "16:9",
})

Error handling

Error	Likely cause	Action
401/403	Missing or invalid API Key	Check env var, must be Beijing region
400 `InvalidParameter`	Bad media combination or missing required params	Validate against model's media rules
"does not support synchronous calls"	Missing `X-DashScope-Async: enable` header	Add required header
429	Rate limit or quota	Retry with backoff

Output location

Default output: output/aliyun-kling-video/videos/
Override base dir with OUTPUT_DIR.

Anti-patterns

Do not use model names other than kling/kling-v3-video-generation or kling/kling-v3-omni-video-generation.
Do not call this API synchronously — async header is required.
Do not use refer, base, or feature media types with the standard model — use omni only.
Do not mix incompatible media combinations.
Video URLs expire; download and persist immediately.
Beijing region only — do not use Singapore endpoint.

Workflow

Confirm user intent: t2v, i2v, reference-to-video, editing, or storyboard.
Select appropriate model (standard for basic t2v/i2v, omni for reference/editing).
Prepare media array with correct types and valid URLs.
Create async task and poll for results.
Download and save generated video before URL expiration.

References

See references/api_reference.md for full HTTP API details.
See references/sources.md for source links.

Files

SKILL.md and 3 other files (scripts, references) in skills/ai/video/aliyun-kling-video of cinience/alicloud-skills.

SKILL.md
references/api_reference.md
references/sources.md
scripts/generate_kling_video.py

Open the folder on GitHubat commit 1818263

Compare with similar skills

Aliyun Kling Video 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.

Aliyun Kling Video compared with similar skills
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Aliyun Kling Video this skillcinience/alicloud-skills	397	—	~2.2k	Automated safety check: Pass	MIT	2 mo ago
Bailian Media Generationmodelstudioai/cli	542	—	~2k	Automated safety check: Pass	Apache-2.0	2 days ago
Video Generationbytedance/deer-flow	84k	3 repos	~1.4k	Automated safety check: Pass	MIT	today
Video Cover Imageitwanger/toBeBetterJavaer	18k	—	~3.3k	Automated safety check: Pass	None	yesterday
Seedancesongguoxs/seedance-prompt-skill	2.9k	1 repos	~2.5k	Automated safety check: Pass	None	8 mo ago
HyperFrames Video Entry Pointheygen-com/hyperframes	60k	3 repos	~5.2k	Automated safety check: Pass	Apache-2.0	today

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cinience/alicloud-skills
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397 GitHub stars~734 tokensUpdated 2 mo ago
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Aliyun Aimiaobi Generate
cinience/alicloud-skills
A skill your agent uses when managing Alibaba Cloud Quan Miao (AiMiaoBi) via OpenAPI/SDK, including the user asks for Alibaba Cloud MiaoBi content operations, including listing resources…
397 GitHub stars~724 tokensUpdated 2 mo ago
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Works with

Alibaba Cloud

Questions about Aliyun Kling Video

What does Aliyun Kling Video do?

A skill your agent uses when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation). Aliyun Kling Video is an agent skill from cinience/alicloud-skills. Use when generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation, kling/kling-v3-omni-video-generation).

When should I use Aliyun Kling Video?

Aliyun Kling Video fits situations like: generating videos with Kling v3 models on DashScope (kling/kling-v3-video-generation; kling/kling-v3-omni-video-generation); implementing text-to-video; reference-to-video.

How do I install Aliyun Kling Video in Claude Code?

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

How do I install Aliyun Kling Video in Codex?

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

Can I use Aliyun Kling Video 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 cinience/alicloud-skills --skill aliyun-kling-video -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aliyun-kling-video, .gemini/skills/aliyun-kling-video, .github/skills/aliyun-kling-video and .opencode/skills/aliyun-kling-video in your project.

What does Aliyun Kling Video need to run?

Going by SKILL.md and its folder, Aliyun Kling Video needs Python for the scripts in its folder, the command-line tools its instructions call (python and python3) and credentials named DASHSCOPE_API_KEY and API_KEY. Our summary lists: Python 3; A credential in DASHSCOPE_API_KEY; A credential in API_KEY.

Does Aliyun Kling Video access the network?

SKILL.md names 2 domains. In commands or code: dashscope.aliyuncs.com; the agent is likely to contact it when it follows the instructions. As links in the text: bailian.console.aliyun.com. This is read from the text; nothing was executed.

Is Aliyun Kling Video 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Aliyun Kling Video use?

Aliyun Kling Video is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Aliyun Kling Video use?

About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.

What are the alternatives to Aliyun Kling Video?

Skills that share tags, products or a category with Aliyun Kling Video: Bailian Media Generation (modelstudioai/cli, 542 stars), Video Generation (bytedance/deer-flow, 84k stars), Video Cover Image (itwanger/toBeBetterJavaer, 18k stars) and Seedance (songguoxs/seedance-prompt-skill, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Aliyun Kling Video?

cinience (a GitHub user) maintains it in cinience/alicloud-skills, which has 397 GitHub stars. The repository holds 96 skills in this directory. The repository was last updated on August 11, 2026.

Source: cinience/alicloud-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 Aliyun Kling Video

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

Kling V3 Video Generation

Validation

Output And Evidence

Prerequisites

Critical model names

Capabilities

API endpoint (async only)

Normalized interface

Request (input)

Request (parameters)

Media input limits

Media combination rules

Response (task creation)

Response (task result)

Quick start (Python + HTTP)

Usage examples

Error handling

Output location

Anti-patterns

Workflow

References

Files

Compare with similar skills

Similar skills

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Related

Questions about Aliyun Kling Video