From klingai-pack
Configures Kling AI team access with per-project API keys, role-based permissions, and Python-enforced daily usage quotas.
How this skill is triggered — by the user, by Claude, or both
Slash command
/klingai-pack:klingai-team-setupThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Manage team access to the Kling AI API using separate API keys, environment-based routing, usage quotas per team member, and centralized credential management.
Manage team access to the Kling AI API using separate API keys, environment-based routing, usage quotas per team member, and centralized credential management.
Create separate API key pairs in the Kling AI developer console for each environment:
| Environment | Key Naming Convention | Purpose |
|---|---|---|
| Development | dev-<project> | Local testing, free tier |
| Staging | staging-<project> | Integration testing |
| Production | prod-<project> | Live traffic |
# .env.development
KLING_ACCESS_KEY="ak_dev_..."
KLING_SECRET_KEY="sk_dev_..."
# .env.production
KLING_ACCESS_KEY="ak_prod_..."
KLING_SECRET_KEY="sk_prod_..."
from dataclasses import dataclass
from typing import Optional
@dataclass
class TeamMember:
name: str
email: str
role: str # admin, editor, viewer
daily_credit_limit: int
allowed_models: list[str]
@dataclass
class TeamConfig:
name: str
members: list[TeamMember]
total_daily_limit: int = 1000
default_model: str = "kling-v2-master"
default_mode: str = "standard"
def get_member(self, email: str) -> Optional[TeamMember]:
return next((m for m in self.members if m.email == email), None)
# Example team configuration
team = TeamConfig(
name="marketing",
total_daily_limit=5000,
members=[
TeamMember("Alice", "[email protected]", "admin", 2000,
["kling-v2-6", "kling-v2-master", "kling-v2-5-turbo"]),
TeamMember("Bob", "[email protected]", "editor", 500,
["kling-v2-master", "kling-v2-5-turbo"]),
TeamMember("Carol", "[email protected]", "viewer", 100,
["kling-v2-5-turbo"]),
],
)
import time
from collections import defaultdict
class TeamQuotaManager:
"""Enforce per-member and team-wide credit limits."""
def __init__(self, config: TeamConfig):
self.config = config
self._usage = defaultdict(int) # email -> credits used today
self._reset_time = time.time()
def _check_reset(self):
if time.time() - self._reset_time > 86400:
self._usage.clear()
self._reset_time = time.time()
def authorize(self, email: str, credits_needed: int, model: str) -> bool:
self._check_reset()
member = self.config.get_member(email)
if not member:
raise PermissionError(f"Unknown user: {email}")
if model not in member.allowed_models:
raise PermissionError(f"{email} not authorized for {model}")
if self._usage[email] + credits_needed > member.daily_credit_limit:
raise RuntimeError(f"{email} exceeds daily limit "
f"({self._usage[email]} + {credits_needed} > {member.daily_credit_limit})")
team_total = sum(self._usage.values()) + credits_needed
if team_total > self.config.total_daily_limit:
raise RuntimeError(f"Team daily limit exceeded ({team_total} > {self.config.total_daily_limit})")
return True
def record_usage(self, email: str, credits: int):
self._usage[email] += credits
def usage_report(self) -> dict:
return {
"team_total": sum(self._usage.values()),
"team_limit": self.config.total_daily_limit,
"by_member": dict(self._usage),
}
| Tool | How to Store AK/SK |
|---|---|
| AWS Secrets Manager | aws secretsmanager create-secret --name kling/prod |
| GCP Secret Manager | gcloud secrets create kling-prod |
| HashiCorp Vault | vault kv put secret/kling ak=... sk=... |
| 1Password CLI | op item create --category login --title "Kling API" |
# Load from AWS Secrets Manager
import boto3
import json
def get_kling_credentials(secret_name="kling/prod"):
client = boto3.client("secretsmanager")
secret = client.get_secret_value(SecretId=secret_name)
creds = json.loads(secret["SecretString"])
return creds["access_key"], creds["secret_key"]
class TeamKlingClient:
"""Kling client with team-level access control."""
def __init__(self, base_client, quota_manager: TeamQuotaManager):
self.client = base_client
self.quotas = quota_manager
def text_to_video(self, email: str, prompt: str, **kwargs):
model = kwargs.get("model", "kling-v2-master")
credits = 10 if kwargs.get("mode") != "professional" else 35
self.quotas.authorize(email, credits, model)
result = self.client.text_to_video(prompt, **kwargs)
self.quotas.record_usage(email, credits)
return result
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin klingai-packProvides production reference architecture for scalable Kling AI video generation platforms, including API gateway, job queues, workers, storage, and monitoring.
Generates videos from text prompts or images, animates still images, and creates talking avatars from photos with audio using Kling AI models (VIDEO 3.0, Avatar 2.0, etc.). Handles multi-shot storyboards, character consistency, and prompt engineering.
Provisions OpenRouter team API keys with per-user credit limits, tracks usage, and enables attribution using management API and Python scripts.