klingai-common-errors
Provides a comprehensive reference for Kling AI API error codes and solutions for generation issues.
Install
mkdir -p .claude/skills/klingai-common-errors && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/7728" && unzip -o skill.zip -d .claude/skills/klingai-common-errors && rm skill.zipInstalls to .claude/skills/klingai-common-errors
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Diagnose and fix common Kling AI API errors. Use when troubleshootingKey capabilities
- →Validate API request parameters
- →Implement exponential backoff for 429 and 5xx errors
- →Manage JWT token refresh cycles
- →Log request and response details for debugging
- →Verify task status and failure reasons
How it works
The skill provides a retry wrapper for HTTP requests and a token manager class that automatically refreshes JWTs before they expire.
Inputs & outputs
When to use klingai-common-errors
- →Resolve 429 rate limit issues
- →Fix 401 unauthorized JWT errors
- →Troubleshoot 500 internal server errors
- →Validate API request payloads
About this skill
Kling AI Common Errors
Overview
Complete error reference for the Kling AI API. Covers HTTP status codes, task-level failures, JWT issues, and generation-specific problems with tested solutions.
HTTP Error Codes
| Code | Error | Cause | Solution |
|---|---|---|---|
400 | Bad Request | Invalid parameters, malformed JSON | Validate all required fields; check model_name is valid |
401 | Unauthorized | Invalid/expired JWT token | Regenerate JWT; verify AK/SK; check exp claim |
402 | Payment Required | Insufficient credits | Top up API resource pack or subscription |
403 | Forbidden | Content policy violation or API disabled | Review prompt against content policy; enable API access |
404 | Not Found | Invalid task_id or wrong endpoint | Verify task_id; check endpoint path spelling |
429 | Too Many Requests | Rate limit exceeded | Implement exponential backoff (see pattern below) |
500 | Internal Server Error | Kling platform issue | Retry after 30s; if persistent, check status page |
502 | Bad Gateway | Upstream service unavailable | Retry with backoff; typically transient |
503 | Service Unavailable | System maintenance | Wait and retry; check announcements |
Task-Level Failures
When HTTP returns 200 but task_status is "failed":
task_status_msg | Cause | Solution |
|---|---|---|
| Content policy violation | Prompt contains restricted content | Remove violent, adult, or copyrighted references |
| Image quality too low | Source image is blurry or too small | Use image >= 300x300px, clear and sharp |
| Prompt too complex | Too many scene elements | Simplify to 1-2 subjects, clear action |
| Generation timeout | Internal processing exceeded limit | Retry; reduce duration from 10s to 5s |
| Invalid image format | Unsupported file type | Use JPG, PNG, or WebP |
| Mask dimension mismatch | Mask size differs from source | Ensure mask matches source image dimensions exactly |
JWT Authentication Errors
Problem: 401 on every request
# WRONG — missing headers parameter
token = jwt.encode(payload, sk, algorithm="HS256")
# CORRECT — include explicit headers
token = jwt.encode(payload, sk, algorithm="HS256",
headers={"alg": "HS256", "typ": "JWT"})
Problem: Token works then fails after 30 min
# WRONG — token generated once at import time
TOKEN = generate_token()
# CORRECT — refresh before expiry
class TokenManager:
def __init__(self, ak, sk):
self.ak, self.sk = ak, sk
self._token = None
self._exp = 0
@property
def token(self):
if time.time() >= self._exp - 300: # 5 min buffer
payload = {"iss": self.ak, "exp": int(time.time()) + 1800,
"nbf": int(time.time()) - 5}
self._token = jwt.encode(payload, self.sk, algorithm="HS256",
headers={"alg": "HS256", "typ": "JWT"})
self._exp = int(time.time()) + 1800
return self._token
Rate Limit Handling
import time
import requests
def request_with_backoff(method, url, headers, json=None, max_retries=5):
"""Retry with exponential backoff on 429 and 5xx errors."""
for attempt in range(max_retries):
response = method(url, headers=headers, json=json)
if response.status_code == 429:
retry_after = int(response.headers.get("Retry-After", 2 ** attempt))
print(f"Rate limited. Retrying in {retry_after}s...")
time.sleep(retry_after)
continue
elif response.status_code >= 500:
wait = 2 ** attempt
print(f"Server error {response.status_code}. Retrying in {wait}s...")
time.sleep(wait)
continue
response.raise_for_status()
return response
raise RuntimeError(f"Max retries ({max_retries}) exceeded")
Diagnostic Checklist
When a generation fails, check in order:
- Auth valid? — Test with a simple GET request first
- Credits available? — Check balance in developer console
- Model valid? — Verify
model_namematches catalog exactly - Parameters valid? —
durationmust be"5"or"10"(string, not int) - Prompt clean? — Remove special characters, keep under 2500 chars
- Image accessible? — For I2V, verify image URL is publicly accessible
- Feature exclusivity? —
image_tail,dynamic_masks, andcamera_controlare mutually exclusive
Debug Logging
import logging
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger("kling")
def debug_request(method, url, headers, json=None):
"""Log request/response for debugging."""
logger.debug(f"→ {method.__name__.upper()} {url}")
logger.debug(f"→ Body: {json}")
r = method(url, headers=headers, json=json)
logger.debug(f"← Status: {r.status_code}")
logger.debug(f"← Body: {r.text[:500]}")
return r
Resources
When not to use it
- →When using prompts containing restricted content
- →When using images smaller than 300x300px
Prerequisites
Limitations
- →Duration must be 5 or 10 as a string
- →Prompts must be under 2500 characters
- →Image tail, dynamic masks, and camera control are mutually exclusive
How it compares
It automates the token lifecycle and error recovery, preventing common 401 and 429 failures found in manual implementations.
Compared to similar skills
klingai-common-errors side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| klingai-common-errors (this skill) | 1 | 27d | Review | Intermediate |
| groq-common-errors | 1 | 27d | Review | Intermediate |
| apollo-common-errors | 1 | 27d | Caution | Intermediate |
| fastapi-templates | 520 | 2mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by jeremylongshore
View all by jeremylongshore →You might also like
groq-common-errors
jeremylongshore
Diagnose and fix Groq common errors and exceptions. Use when encountering Groq errors, debugging failed requests, or troubleshooting integration issues. Trigger with phrases like "groq error", "fix groq", "groq not working", "debug groq".
apollo-common-errors
jeremylongshore
Diagnose and fix common Apollo.io API errors. Use when encountering Apollo API errors, debugging integration issues, or troubleshooting failed requests. Trigger with phrases like "apollo error", "apollo api error", "debug apollo", "apollo 401", "apollo 429", "apollo troubleshoot".
fastapi-templates
wshobson
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
mcp-builder
anthropics
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
python-testing-patterns
wshobson
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
fastapi-pro
sickn33
Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.