Klingai Video Extension
Extend video duration using Kling AI continuation.
by jeremylongshore · MIT
The skill
Extend video duration using Kling AI continuation. Use when creating longer videos from shorter clips or building sequences. Trigger with phrases like 'klingai extend video', 'kling ai video continuation', 'klingai longer video', 'extend klingai clip'.
Kling AI Video Extension
Overview
Extend an existing video by appending additional seconds. The extension endpoint takes the task_id of a completed video and generates a seamless continuation.
Endpoint: POST https://api.klingai.com/v1/videos/video-extend
Request Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
task_id |
string | Yes | Task ID of the completed source video |
prompt |
string | No | Motion/scene description for extension |
duration |
string | No | Extension length: "5" (default) |
mode |
string | No | "standard" or "professional" |
model_name |
string | No | Default: "kling-v2-master" |
callback_url |
string | No | Webhook for completion |
Basic Extension
import jwt, time, os, requests
BASE = "https://api.klingai.com/v1"
def get_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"}
# Step 1: Generate the initial 5s video
initial = requests.post(f"{BASE}/videos/text2video", headers=get_headers(), json={
"model_name": "kling-v2-master",
"prompt": "A rocket launching from a desert landscape, cinematic",
"duration": "5",
"mode": "standard",
}).json()
initial_task_id = initial["data"]["task_id"]
# Wait for completion...
# (poll until task_status == "succeed")
# Step 2: Extend by 5 more seconds
extension = requests.post(f"{BASE}/videos/video-extend", headers=get_headers(), json={
"task_id": initial_task_id,
"prompt": "The rocket ascends through clouds into the stratosphere",
"duration": "5",
"mode": "standard",
}).json()
ext_task_id = extension["data"]["task_id"]
# Step 3: Poll extension task
while True:
time.sleep(15)
result = requests.get(
f"{BASE}/videos/video-extend/{ext_task_id}", headers=get_headers()
).json()
if result["data"]["task_status"] == "succeed":
extended_url = result["data"]["task_result"]["videos"][0]["url"]
print(f"Extended video: {extended_url}")
break
elif result["data"]["task_status"] == "failed":
print(f"Failed: {result['data']['task_status_msg']}")
break
Chain Multiple Extensions
def chain_extensions(initial_task_id: str, prompts: list[str],
duration: str = "5", mode: str = "standard") -> list[str]:
"""Chain multiple extensions to build a longer video."""
current_task_id = initial_task_id
video_urls = []
for i, prompt in enumerate(prompts):
print(f"Extension {i + 1}/{len(prompts)}: submitting...")
# Submit extension
r = requests.post(f"{BASE}/videos/video-extend", headers=get_headers(), json={
"task_id": current_task_id,
"prompt": prompt,
"duration": duration,
"mode": mode,
}).json()
ext_task_id = r["data"]["task_id"]
# Poll for completion
while True:
time.sleep(15)
result = requests.get(
f"{BASE}/videos/video-extend/{ext_task_id}", headers=get_headers()
).json()
status = result["data"]["task_status"]
if status == "succeed":
url = result["data"]["task_result"]["videos"][0]["url"]
video_urls.append(url)
current_task_id = ext_task_id # next extension chains from this
print(f"Extension {i + 1} complete: {url}")
break
elif status == "failed":
raise RuntimeError(f"Extension {i + 1} failed: {result['data']['task_status_msg']}")
return video_urls
Usage: Build a 20-Second Video
# Generate initial 5s
initial_r = requests.post(f"{BASE}/videos/text2video", headers=get_headers(), json={
"model_name": "kling-v2-master",
"prompt": "Morning sunrise over a mountain lake, mist rising",
"duration": "5",
"mode": "standard",
}).json()
initial_id = initial_r["data"]["task_id"]
# ... poll until complete ...
# Chain 3 more extensions = 5 + 5 + 5 + 5 = 20 seconds total
extensions = chain_extensions(initial_id, [
"Sun rises higher, birds begin flying across the lake",
"A deer approaches the water's edge to drink",
"Wide shot pulling back to reveal the full mountain range",
])
Cost
Each extension costs the same as a new generation:
| Extension Duration | Standard | Professional |
|---|---|---|
| 5 seconds | 10 credits | 35 credits |
A 20-second video (initial + 3 extensions) costs 40 credits in standard mode.
Error Handling
| Error | Cause | Fix |
|---|---|---|
Invalid task_id |
Source task doesn't exist | Verify task_id is from a completed generation |
| Source not complete | Extending a task still processing | Wait for source task to reach succeed status |
| Extension failed | Prompt conflict with source | Align extension prompt with original scene |
Prerequisites
- A completed, rights-cleared or synthetic source draft, approved extension brief, authorized workspace and credit budget, policy review, draft-only destination, and a rollback/removal owner.
Instructions
- Confirm source ownership, completion state, and approved continuity brief before creating an extension; do not use private, unlicensed, or policy-restricted material.
- Submit one watermarked draft canary within the approved duration and credit cap, then verify policy, rights, quality, and destination controls.
- Halt on continuity, policy, rights, or budget drift and delete the extension task instead of publishing it.
- Promote only after owner approval; retain a redacted receipt and remove temporary assets at the agreed retention boundary.
Output
Produce an extension receipt with source task reference, rights classification, mode/duration, credit estimate, policy review, draft destination, approver, retention/removal reference, and task ID. Exclude prompts, identities, and asset URLs.
Examples
source=synthetic-task-42; rights=cleared; duration=5s; mode=standard; policy=pass; destination=draft-only; cleanup=24h is safe for review.
Resources
Use this skill
Connect your agent to the Skill Store MCP server and ask for it by ref: jeremylongshore/klingai-video-extension-81787877115.
Details
- Publisher
- jeremylongshore
- Category
- Creative & Media › Video
- License
- MIT
- Updated
- 2026-10-19
References
More from jeremylongshore
- Agency Os Notion-as-source-of-truth dispatch board for running your work like an AI agency.
- Audit Use when the user wants a code review on recent changes — quality, spec, security, or performance…
- Background Use when the user wants to see, inspect, cancel, or prune background agents fired during prior ch…
- Bridge Use when the user wants hyperflow's behavioral rules to apply outside the terminal CLI — in Claud…