Animate static images into video using Kling AI. Use when converting images to video,
adding motion to stills, or building I2V pipelines. Trigger with phrases like 'klingai image to video',
'kling ai animate image', 'klingai img2vid', 'animate picture klingai'.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
A direct command skips the review prompt. Inspect the source before running it.
Animate static images into video using Kling AI. Use when converting images to video,
adding motion to stills, or building I2V pipelines. Trigger with phrases like 'klingai image to video',
'kling ai animate image', 'klingai img2vid', 'animate picture klingai'.
Designed for Claude Code, also compatible with Codex and OpenClaw
Kling AI Image-to-Video
Overview
Animate static images using the /v1/videos/image2video endpoint. Supports motion prompts, camera control, dynamic masks (motion brush), static masks, and tail images for start-to-end transitions.
End-frame image URL (mutually exclusive with masks/camera)
camera_control
object
No
Camera movement (mutually exclusive with masks/image_tail)
static_mask
string
No
Mask image URL for fixed regions
dynamic_masks
array
No
Motion brush trajectories
callback_url
string
No
Webhook for completion
Basic Image-to-Video
import jwt, time, os, requests
BASE = "https://api.klingai.com/v1"defget_headers():
ak, sk = os.environ["KLING_ACCESS_KEY"], os.environ["KLING_SECRET_KEY"]
token = jwt.encode(
{"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5},
sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"}
)
return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
# Animate a landscape photo
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
"model_name": "kling-v2-1",
"image": "https://example.com/landscape.jpg",
"prompt": "Clouds slowly drifting across the sky, gentle wind rustling through trees",
"negative_prompt": "static, frozen, blurry",
"duration": "5",
"mode": "standard",
})
task_id = response.json()["data"]["task_id"]
# Poll for resultwhileTrue:
time.sleep(15)
result = requests.get(
f"{BASE}/videos/image2video/{task_id}", headers=get_headers()
).json()
if result["data"]["task_status"] == "succeed":
print(f"Video: {result['data']['task_result']['videos'][0]['url']}")
breakelif result["data"]["task_status"] == "failed":
raise RuntimeError(result["data"]["task_status_msg"])
Start-to-End Transition (image_tail)
Use image_tail to specify both the first and last frame. Kling interpolates the motion between them.
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
"model_name": "kling-v2-master",
"image": "https://example.com/sunrise.jpg", # first frame"image_tail": "https://example.com/sunset.jpg", # last frame"prompt": "Time lapse of sun moving across the sky",
"duration": "5",
"mode": "professional",
})
Motion Brush (dynamic_masks)
Draw motion paths for specific elements in the image. Up to 6 motion paths per image in v2.6.
