Agent skill

Aliyun Happyhorse I2v

A skill your agent uses when generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v).

MITAuto-check passedMedia & Creative

Install Aliyun Happyhorse I2v

skills CLI

$ npx skills add cinience/alicloud-skills --skill aliyun-happyhorse-i2v -a claude-code

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-happyhorse-i2v --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-happyhorse-i2v .claude/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .claude/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v

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-happyhorse-i2v -a codex

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-happyhorse-i2v --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-happyhorse-i2v .agents/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .agents/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v -a cursor

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-happyhorse-i2v --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-happyhorse-i2v .cursor/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .cursor/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v

--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-happyhorse-i2v -a gemini-cli

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

GitHub CLI

$ gh skill install cinience/alicloud-skills aliyun-happyhorse-i2v --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-happyhorse-i2v .gemini/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .gemini/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v

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-happyhorse-i2v -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-happyhorse-i2v .github/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .github/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v -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-happyhorse-i2v --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-happyhorse-i2v .opencode/skills/aliyun-happyhorse-i2v && 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-happyhorse-i2v" agent skill from https://github.com/cinience/alicloud-skills/tree/main/skills/ai/video/aliyun-happyhorse-i2v into .opencode/skills/aliyun-happyhorse-i2v/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aliyun-happyhorse-i2v", 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-happyhorse-i2v
GitHub stars: 397
Token cost: ~1.8k tokens
SKILL.md length: 506 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 from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v).

Works in 4 steps: Confirm intent: single first-frame image… → Validate the image meets format / size /… → Create async task and poll… → …
Generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v)
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 and cdn.translate.alibaba.com; needs DASHSCOPE_API_KEY and API_KEY

What it does

Aliyun Happyhorse I2v is an agent skill from cinience/alicloud-skills. Use when generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v). Use when implementing first-frame video generation with optional text guidance via the video-synthesis async API on Alibaba Cloud Model Studio.

Its SKILL.md is about 1.8k 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/i2v_happyhorse.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 from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v)
Implementing first-frame video generation with optional text guidance via the video-synthesis async API on Alibaba Cloud Model Studio

Example prompts

“/aliyun-happyhorse-i2v”

Requirements

Python 3
A credential in DASHSCOPE_API_KEY
A credential in API_KEY

Workflow steps

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

Confirm intent: single first-frame image with optional text prompt.
Validate the image meets format / size / resolution / aspect-ratio limits.
Create async task and poll /tasks/{task_id} every ~15s.
Download output.video_url before the 24-hour 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
- cdn.translate.alibaba.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 Happyhorse I2v loads about 1.8k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 74 tokens; SKILL.md has 506 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: ~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3k

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). 506 words, ~1,831 tokens.

Download SKILL.mdSave it as .claude/skills/aliyun-happyhorse-i2v/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.

name: aliyun-happyhorse-i2v
description: Use when generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v). Use when implementing first-frame video generation with optional text guidance via the video-synthesis async API on Alibaba Cloud Model Studio.

HappyHorse 1.0 Image-to-Video (First Frame)

Validation

bash

mkdir -p output/aliyun-happyhorse-i2v
python -m py_compile skills/ai/video/aliyun-happyhorse-i2v/scripts/i2v_happyhorse.py && echo "py_compile_ok" > output/aliyun-happyhorse-i2v/validate.txt

Pass criteria: command exits 0 and output/aliyun-happyhorse-i2v/validate.txt is generated.

Output And Evidence

Save task IDs, polling responses, and final video URLs to output/aliyun-happyhorse-i2v/.
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, or add dashscope_api_key to ~/.alibabacloud/credentials.

Critical model names

happyhorse-1.0-i2v — first-frame image-to-video; output aspect ratio follows the input image automatically

Capabilities

Capability	Description	Required media
First-frame video	Generate a video from one first-frame image, optionally guided by a text prompt	`first_frame` (exactly 1)

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

Singapore endpoint: replace dashscope.aliyuncs.com with dashscope-intl.aliyuncs.com.

Polling endpoint: GET https://dashscope.aliyuncs.com/api/v1/tasks/{task_id} — recommended interval 15s.

Normalized interface

Request

model (string, required) — fixed happyhorse-1.0-i2v
input.prompt (string, optional) — up to 5000 non-CJK / 2500 CJK characters
input.media (array, required) — exactly one element with:
- type: first_frame
- url: public HTTP/HTTPS URL of the first-frame image
parameters.resolution (string, optional) — 720P or 1080P (default: 1080P)
parameters.duration (integer, optional) — video length in seconds, range [3, 15] (default: 5)
parameters.watermark (boolean, optional) — bottom-right "Happy Horse" watermark (default: true)
parameters.seed (integer, optional) — range [0, 2147483647]

The output video aspect ratio follows the input first-frame image; ratio is not supported for i2v.

Media input limits

First-frame image (type=first_frame):

Formats: JPEG, JPG, PNG, WEBP
Resolution: width and height ≥ 300 pixels
Aspect ratio: 1:2.5 ~ 2.5:1
Max size: 10 MB

Response (task creation)

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

Response (task result, on SUCCEEDED)

output.video_url (string) — generated MP4 (H.264, 24fps) URL, valid 24 hours
output.orig_prompt (string)
output.submit_time / output.scheduled_time / output.end_time (string)
usage.duration (integer) — billable duration in seconds
usage.output_video_duration (integer)
usage.input_video_duration (integer) — fixed 0 for i2v
usage.SR (integer) — output resolution tier
usage.video_count (integer) — fixed 1

Quick start (Python + HTTP)

python

import os
import time
import requests

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


def create_i2v_task(req: dict) -> str:
    """Create an image-to-video task and return task_id."""
    payload = {
        "model": "happyhorse-1.0-i2v",
        "input": {
            "prompt": req.get("prompt", ""),
            "media": [{"type": "first_frame", "url": req["first_frame_url"]}],
        },
        "parameters": {
            "resolution": req.get("resolution", "1080P"),
            "duration": req.get("duration", 5),
            "watermark": req.get("watermark", True),
        },
    }
    if req.get("seed") is not None:
        payload["parameters"]["seed"] = req["seed"]

    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()
    return resp.json()["output"]["task_id"]


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

Usage examples

python

# Minimal — first-frame only
task_id = create_i2v_task({
    "first_frame_url": "https://cdn.translate.alibaba.com/r/wanx-demo-1.png",
    "prompt": "一只猫在草地上奔跑",
    "duration": 5,
})

# 720P with custom seed for reproducibility
task_id = create_i2v_task({
    "first_frame_url": "https://example.com/portrait.jpg",
    "prompt": "Slow head turn, soft window light",
    "resolution": "720P",
    "duration": 8,
    "seed": 42,
})

Show full SKILL.md (209 more words)Show less

Error handling

Error	Likely cause	Action
401 / `InvalidApiKey`	Missing or invalid `DASHSCOPE_API_KEY`	Check env var or credentials file
400 `InvalidParameter`	Wrong resolution, duration out of [3,15], image too small or wrong format	Validate parameters and image
`current user api does not support synchronous calls`	Missing `X-DashScope-Async: enable` header	Add the required header
`task_status: UNKNOWN`	task_id older than 24 hours	Re-create the task
429	RPS or quota exceeded	Retry with backoff; query RPS default 20

Output location

Default output: output/aliyun-happyhorse-i2v/videos/
Override base dir with OUTPUT_DIR.

Anti-patterns

Do not use any model ID other than happyhorse-1.0-i2v.
Do not call this API synchronously — async header is required.
Do not pass ratio — output aspect ratio follows the first-frame image automatically.
Do not pass more than 1 first-frame, or any last_frame / reference_image / video — only first_frame is supported.
Video URLs expire after 24 hours; download and persist immediately.
Do not use this skill for pure text-to-video (use aliyun-happyhorse-t2v), reference-image fusion (aliyun-happyhorse-r2v), or video editing (aliyun-happyhorse-videoedit).

Workflow

Confirm intent: single first-frame image with optional text prompt.
Validate the image meets format / size / resolution / aspect-ratio limits.
Create async task and poll /tasks/{task_id} every ~15s.
Download output.video_url before the 24-hour 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-happyhorse-i2v of cinience/alicloud-skills.

SKILL.md
references/api_reference.md
references/sources.md
scripts/i2v_happyhorse.py

Open the folder on GitHubat commit 1818263

Compare with similar skills

Aliyun Happyhorse I2v 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 Happyhorse I2v compared with similar skills
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Aliyun Happyhorse I2v this skillcinience/alicloud-skills	397	—	~1.8k	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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Works with

Alibaba Cloud

Questions about Aliyun Happyhorse I2v

What does Aliyun Happyhorse I2v do?

A skill your agent uses when generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v). Aliyun Happyhorse I2v is an agent skill from cinience/alicloud-skills.0-i2v).

When should I use Aliyun Happyhorse I2v?

Aliyun Happyhorse I2v fits situations like: generating videos from a single first-frame image with DashScope HappyHorse 1.0 image-to-video model (happyhorse-1.0-i2v); implementing first-frame video generation with optional text guidance via the video-synthesis async API on Alibaba Cloud Model Studio.

How do I install Aliyun Happyhorse I2v in Claude Code?

Run `npx skills add cinience/alicloud-skills --skill aliyun-happyhorse-i2v -a claude-code`. Or copy the skill folder (skills/ai/video/aliyun-happyhorse-i2v in cinience/alicloud-skills) into .claude/skills/aliyun-happyhorse-i2v in your project. Claude Code loads it when a task matches its description.

How do I install Aliyun Happyhorse I2v in Codex?

Run `npx skills add cinience/alicloud-skills --skill aliyun-happyhorse-i2v -a codex`. Or copy the skill folder (skills/ai/video/aliyun-happyhorse-i2v in cinience/alicloud-skills) into .agents/skills/aliyun-happyhorse-i2v in your project. Codex loads it when a task matches its description.

Can I use Aliyun Happyhorse I2v 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-happyhorse-i2v -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-happyhorse-i2v, .gemini/skills/aliyun-happyhorse-i2v, .github/skills/aliyun-happyhorse-i2v and .opencode/skills/aliyun-happyhorse-i2v in your project.

What does Aliyun Happyhorse I2v need to run?

Going by SKILL.md and its folder, Aliyun Happyhorse I2v 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 Happyhorse I2v access the network?

SKILL.md names 2 domains. In commands or code: dashscope.aliyuncs.com and cdn.translate.alibaba.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Aliyun Happyhorse I2v 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 Happyhorse I2v use?

Aliyun Happyhorse I2v 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 Happyhorse I2v use?

About 1.8k tokens (SKILL.md is roughly 7.3k 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 Happyhorse I2v?

Skills that share tags, products or a category with Aliyun Happyhorse I2v: 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 Happyhorse I2v?

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 Happyhorse I2v

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

HappyHorse 1.0 Image-to-Video (First Frame)

Validation

Output And Evidence

Prerequisites

Critical model names

Capabilities

API endpoint (async only)

Normalized interface

Request

Media input limits

Response (task creation)

Response (task result, on SUCCEEDED)

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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Questions about Aliyun Happyhorse I2v