Klingai Hello World

What it does

When your agent uses it

• Learning Kling AI
• Testing your setup
• With phrases like kling ai hello world
• First kling video

Example prompts

• “kling ai hello world”
• “first kling video”
• “klingai quickstart”
• “/klingai-hello-world”

Requirements

• Python 3
• Node.js
• A credential in KLING_ACCESS_KEY
• A credential in KLING_SECRET_KEY
• Compatibility (from SKILL.md): Designed for Claude Code
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash(npm:*), Grep

Workflow steps

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

1. 1Run the first request in a sandbox using a synthetic or rights-cleared brief and an approved credit cap; never paste credentials into code…
2. 2Request one watermarked, draft-only canary and verify the task state, policy outcome, rights status, and destination before review.
3. 3Cancel and remove the draft if quality, policy, attribution, or budget checks fail; do not publish from the smoke test.
4. 4Record only a redacted receipt and delete temporary assets at the approved retention boundary.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit
  • Bash(npm:*)
  • Grep

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are python, javascript and json).

  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:

  • api.klingai.com
  • cdn.klingai.com

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names these keys or tokens, usually read from environment variables:

  • KLING_ACCESS_KEY
  • KLING_SECRET_KEY

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Designed for Claude Code

  From compatibility in the SKILL.md frontmatter.

Context cost

Klingai Hello World loads about 1.5k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~64

When it runs · the whole SKILL.md, loaded when a task matches

~1.5k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~5.2k

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

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 309 words, ~1,519 tokens.

name

klingai-hello-world

description

Create your first Kling AI video generation with a minimal working example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling video', 'klingai quickstart', 'test klingai'.

allowed-tools

Read, Write, Edit, Bash(npm:*), Grep

compatibility

Designed for Claude Code

version

1.18.0

license

MIT

author

Jeremy Longshore <jeremy@intentsolutions.io>

tags

saas, kling-ai, quickstart

import jwt, time, os, requests

# --- Auth ---
def get_token():
    ak = os.environ["KLING_ACCESS_KEY"]
    sk = os.environ["KLING_SECRET_KEY"]
    payload = {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5}
    return jwt.encode(payload, sk, algorithm="HS256",
                      headers={"alg": "HS256", "typ": "JWT"})

BASE = "https://api.klingai.com/v1"
HEADERS = {"Authorization": f"Bearer {get_token()}", "Content-Type": "application/json"}

# --- Step 1: Create task ---
task = requests.post(f"{BASE}/videos/text2video", headers=HEADERS, json={
    "model_name": "kling-v2-master",
    "prompt": "A golden retriever running through autumn leaves in slow motion, cinematic lighting",
    "duration": "5",
    "aspect_ratio": "16:9",
    "mode": "standard",
}).json()

task_id = task["data"]["task_id"]
print(f"Task created: {task_id}")

# --- Step 2: Poll until complete ---
import time as t
while True:
    t.sleep(10)
    status = requests.get(f"{BASE}/videos/text2video/{task_id}", headers=HEADERS).json()
    state = status["data"]["task_status"]
    print(f"Status: {state}")
    if state == "succeed":
        video_url = status["data"]["task_result"]["videos"][0]["url"]
        print(f"Video ready: {video_url}")
        break
    elif state == "failed":
        print(f"Failed: {status['data']['task_status_msg']}")
        break

import jwt from "jsonwebtoken";

const BASE = "https://api.klingai.com/v1";

function getHeaders() {
  const token = jwt.sign(
    { iss: process.env.KLING_ACCESS_KEY, exp: Math.floor(Date.now() / 1000) + 1800,
      nbf: Math.floor(Date.now() / 1000) - 5 },
    process.env.KLING_SECRET_KEY,
    { algorithm: "HS256", header: { typ: "JWT" } }
  );
  return { Authorization: `Bearer ${token}`, "Content-Type": "application/json" };
}

// Create task
const res = await fetch(`${BASE}/videos/text2video`, {
  method: "POST",
  headers: getHeaders(),
  body: JSON.stringify({
    model_name: "kling-v2-master",
    prompt: "A golden retriever running through autumn leaves in slow motion",
    duration: "5",
    aspect_ratio: "16:9",
    mode: "standard",
  }),
});
const { data } = await res.json();
console.log(`Task: ${data.task_id}`);

// Poll
const poll = setInterval(async () => {
  const r = await fetch(`${BASE}/videos/text2video/${data.task_id}`, { headers: getHeaders() });
  const s = await r.json();
  if (s.data.task_status === "succeed") {
    console.log("Video:", s.data.task_result.videos[0].url);
    clearInterval(poll);
  } else if (s.data.task_status === "failed") {
    console.error("Failed:", s.data.task_status_msg);
    clearInterval(poll);
  }
}, 10000);

{
  "code": 0,
  "message": "success",
  "data": {
    "task_id": "abc123...",
    "task_status": "succeed",
    "task_result": {
      "videos": [{
        "id": "vid_001",
        "url": "https://cdn.klingai.com/...",
        "duration": "5.0"
      }]
    }
  }
}

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/.curated/klingai-hello-world of jeremylongshore/tons-of-skills-marketplace.

• SKILL.md
• references/curl-example.md
• references/errors.md
• references/examples.md
• references/minimal-python-example.md
• references/minimal-typescript-example.md

Open the folder on GitHubat commit cfae287