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jeremylongshore/tons-of-skills-marketplace

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''.

Qu'est-ce que tons-of-skills-marketplace ?

tons-of-skills-marketplace is a Claude Code agent skill that 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''.

Compatible avec✓Claude Code~Codex CLI~Cursor
npx skills add https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/HEAD/plugins/saas-packs/klingai-pack/skills/klingai-video-extension

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Documentation

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

ParameterTypeRequiredDescription
task_idstringYesTask ID of the completed source video
promptstringNoMotion/scene description for extension
durationstringNoExtension length: "5" (default)
modestringNo"standard" or "professional"
model_namestringNoDefault: "kling-v2-master"
callback_urlstringNoWebhook 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 DurationStandardProfessional
5 seconds10 credits35 credits

A 20-second video (initial + 3 extensions) costs 40 credits in standard mode.

Error Handling

ErrorCauseFix
Invalid task_idSource task doesn't existVerify task_id is from a completed generation
Source not completeExtending a task still processingWait for source task to reach succeed status
Extension failedPrompt conflict with sourceAlign 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

  1. Confirm source ownership, completion state, and approved continuity brief before creating an extension; do not use private, unlicensed, or policy-restricted material.
  2. Submit one watermarked draft canary within the approved duration and credit cap, then verify policy, rights, quality, and destination controls.
  3. Halt on continuity, policy, rights, or budget drift and delete the extension task instead of publishing it.
  4. 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

Individual skills in this repo

This repo contains 7 individual skills — each has its own dedicated page.

jeremylongshore/tons-of-skills-marketplace

Generate polished demo videos from a single prompt. Use when the user asks to create a demo video, product walkthrough, feature showcase, or animated presentation. Trigger with "make a demo video", "create a product video", "demo walkthrough", or "feature showcase video".

jeremylongshore/tons-of-skills-marketplace

Runs the full release workflow for the current project. Commits any uncommitted changes, pushes to remote, creates and merges a PR if on a feature branch, determines the next semver version from conventional commits, creates an annotated git tag and GitHub release with generated notes, cleans up merged branches, and returns to a clean main. Use when the user says promote, ship, release, commit and push, tag and release, or get back to main.

jeremylongshore/tons-of-skills-marketplace

Agent skill at plugins/productivity/content-multiplier/skills/channel-formats/SKILL.md

jeremylongshore/tons-of-skills-marketplace

Operate an evidence-backed editorial queue, balance topic and format coverage, schedule approved drafts, and reconcile backlog state with the publishing system. Use when choosing or scheduling the next blog work. Trigger with "show the editorial calendar" or "pick the next topic".

jeremylongshore/tons-of-skills-marketplace

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''.

jeremylongshore/tons-of-skills-marketplace

Generate videos from text prompts with Kling AI. Use when creating videos from descriptions, learning prompt techniques, or building T2V pipelines. Trigger with phrases like ''kling ai text to video'', ''klingai prompt'', ''generate video from text'', ''text2video kling''.

jeremylongshore/tons-of-skills-marketplace

Manage multi-file edits with Cascade coordination. Activate when users mention "multi-file edit", "edit multiple files", "cross-file changes", "refactor across files", or "batch modifications". Handles coordinated multi-file operations. Use when working with windsurf multi file editing functionality. Trigger with phrases like "windsurf multi file editing", "windsurf editing", "windsurf".

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