klingai-prod-checklist

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Source

Execute pre-launch production readiness checklist for Kling AI. Use when preparing to deploy video generation to production. Trigger with phrases like 'klingai production', 'kling ai go-live', 'klingai launch checklist', 'deploy klingai'.

Install

mkdir -p .claude/skills/klingai-prod-checklist && curl -L -o skill.zip "https://mcp.directory/api/skills/download/6859" && unzip -o skill.zip -d .claude/skills/klingai-prod-checklist && rm skill.zip

Installs to .claude/skills/klingai-prod-checklist

About this skill

Kling AI Production Checklist

Overview

Checklist covering authentication, error handling, cost controls, monitoring, security, and content policy before deploying Kling AI video generation to production.

Authentication

  • AK/SK stored in secrets manager (not .env in repo)
  • JWT auto-refresh with 5-min buffer before 30-min expiry
  • Separate API keys per environment (dev/staging/prod)
  • Key rotation schedule (quarterly minimum)
  • Authorization: Bearer <token> format verified

Error Handling

  • HTTP 400/401/402/403/429/5xx all handled
  • Exponential backoff with jitter for 429/5xx retries
  • Max retry limit set (3-5, not infinite)
  • task_status: "failed" logs task_status_msg
  • 30s timeout on all HTTP calls
  • duration sent as string "5" not integer 5

Cost Controls

  • Daily credit budget enforced in code
  • Alert at 80% daily budget consumption
  • standard mode used for non-final renders
  • Max poll attempts cap (no infinite loops)
  • Credit estimate before batch submission
# Pre-batch credit check
credits_needed = len(prompts) * 10  # 10 credits per 5s standard
if credits_needed > DAILY_BUDGET:
    raise RuntimeError(f"Batch needs {credits_needed}, budget is {DAILY_BUDGET}")

Task Management

  • All task_ids logged with timestamp
  • Stuck task detection (>10 min in processing)
  • callback_url used instead of polling in production
  • Failed tasks queued for retry
  • Video URLs downloaded promptly (Kling CDN URLs expire)

Content Safety

  • Prompts validated before API submission
  • User-generated prompts sanitized
  • Default negative prompt includes safety terms
  • Content moderation on user-facing apps
  • Policy violation errors handled gracefully

Security

  • API keys never logged (redacted in debug output)
  • Video URLs treated as temporary (store on own CDN)
  • Webhook endpoints HTTPS-only
  • Rate limiting on your API layer
  • No sensitive data in prompt strings

Monitoring

  • API latency tracked per endpoint
  • Success/failure rate dashboard
  • Credit consumption metrics
  • Alert on >5% failure rate
  • Structured JSON logs for all API calls

Performance

  • Connection pooling via requests.Session()
  • Concurrent tasks within API tier limit
  • Video downloads async/background
  • Generated videos CDN-cached
# Connection pooling
session = requests.Session()
adapter = requests.adapters.HTTPAdapter(pool_connections=5, pool_maxsize=10)
session.mount("https://", adapter)

Pre-Launch Smoke Test

from kling_client import KlingClient

c = KlingClient()
result = c.text_to_video("test: blue sky with clouds", duration=5, mode="standard")
assert result["videos"][0]["url"], "No video URL"
print("READY FOR PRODUCTION")

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