Klingai Install Auth

What it does

When your agent uses it

• Starting a new Kling AI integration
• Troubleshooting auth issues
• With phrases like kling ai setup
• Klingai api key

Example prompts

• “kling ai setup”
• “klingai api key”
• “kling ai authentication”
• “/klingai-install-auth”

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

3 steps, taken from the step headings in SKILL.md.

1. 1Get Credentials
2. 2Generate JWT Token
3. 3Verify Authentication

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, bash and javascript).

  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

  Also links to:

  • 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 Install Auth loads about 1.5k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 350 words of instructions outside code blocks.

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

~65

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

~2.2k

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

• NoteMentions a .env fileSKILL.md:45

  # .env file

• NoteMentions a .env fileSKILL.md:164

  - Use `.env` files with `.gitignore` exclusion

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). 350 words, ~1,484 tokens.

name

klingai-install-auth

description

Set up Kling AI API authentication with JWT tokens. Use when starting a new Kling AI integration or troubleshooting auth issues. Trigger with phrases like 'kling ai setup', 'klingai api key', 'kling ai authentication', 'configure 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, api, authentication

# .env file
KLING_ACCESS_KEY="ak_your_access_key_here"
KLING_SECRET_KEY="sk_your_secret_key_here"

import jwt
import time
import os

def generate_kling_token():
    """Generate a JWT token for Kling AI API authentication."""
    ak = os.environ["KLING_ACCESS_KEY"]
    sk = os.environ["KLING_SECRET_KEY"]

    headers = {"alg": "HS256", "typ": "JWT"}
    payload = {
        "iss": ak,
        "exp": int(time.time()) + 1800,  # 30 min expiry
        "nbf": int(time.time()) - 5,     # valid 5s ago (clock skew)
    }

    return jwt.encode(payload, sk, algorithm="HS256", headers=headers)

token = generate_kling_token()
# Use: Authorization: Bearer <token>

import jwt from "jsonwebtoken";

function generateKlingToken() {
  const ak = process.env.KLING_ACCESS_KEY;
  const sk = process.env.KLING_SECRET_KEY;

  const payload = {
    iss: ak,
    exp: Math.floor(Date.now() / 1000) + 1800,
    nbf: Math.floor(Date.now() / 1000) - 5,
  };

  return jwt.sign(payload, sk, { algorithm: "HS256", header: { typ: "JWT" } });
}

import requests

BASE_URL = "https://api.klingai.com/v1"
token = generate_kling_token()

response = requests.get(
    f"{BASE_URL}/videos/text2video",  # any endpoint to test auth
    headers={"Authorization": f"Bearer {token}"},
)

if response.status_code == 401:
    print("Auth failed — check AK/SK values")
elif response.status_code in (200, 400):
    print("Auth working — credentials valid")

import time

class KlingAuth:
    """Auto-refreshing JWT token manager."""

    def __init__(self, access_key: str, secret_key: str, buffer_sec: int = 300):
        self.ak = access_key
        self.sk = secret_key
        self.buffer = buffer_sec  # refresh 5 min before expiry
        self._token = None
        self._expires_at = 0

    @property
    def token(self) -> str:
        if time.time() >= (self._expires_at - self.buffer):
            self._refresh()
        return self._token

    def _refresh(self):
        now = int(time.time())
        payload = {"iss": self.ak, "exp": now + 1800, "nbf": now - 5}
        self._token = jwt.encode(payload, self.sk, algorithm="HS256",
                                  headers={"alg": "HS256", "typ": "JWT"})
        self._expires_at = now + 1800

    @property
    def headers(self) -> dict:
        return {
            "Authorization": f"Bearer {self.token}",
            "Content-Type": "application/json",
        }

© 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 3 other files (references) in skills/.curated/klingai-install-auth of jeremylongshore/tons-of-skills-marketplace.

• SKILL.md
• references/environment-setup.md
• references/errors.md
• references/examples.md

Open the folder on GitHubat commit cfae287