klingai-common-errors
Diagnose and fix common Kling AI API errors. Use when troubleshooting failed video generation or API issues. Trigger with phrases like 'kling ai error', 'klingai not working', 'fix klingai', 'klingai failed'.
Best use case
klingai-common-errors is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Diagnose and fix common Kling AI API errors. Use when troubleshooting failed video generation or API issues. Trigger with phrases like 'kling ai error', 'klingai not working', 'fix klingai', 'klingai failed'.
Teams using klingai-common-errors should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/klingai-common-errors/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How klingai-common-errors Compares
| Feature / Agent | klingai-common-errors | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Diagnose and fix common Kling AI API errors. Use when troubleshooting failed video generation or API issues. Trigger with phrases like 'kling ai error', 'klingai not working', 'fix klingai', 'klingai failed'.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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
```python
# 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
```python
# 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
```python
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:
1. **Auth valid?** — Test with a simple GET request first
2. **Credits available?** — Check balance in developer console
3. **Model valid?** — Verify `model_name` matches catalog exactly
4. **Parameters valid?** — `duration` must be `"5"` or `"10"` (string, not int)
5. **Prompt clean?** — Remove special characters, keep under 2500 chars
6. **Image accessible?** — For I2V, verify image URL is publicly accessible
7. **Feature exclusivity?** — `image_tail`, `dynamic_masks`, and `camera_control` are mutually exclusive
## Debug Logging
```python
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
- [API Reference](https://app.klingai.com/global/dev/document-api/apiReference/model/textToVideo)
- [Content Policy](https://app.klingai.com/global/dev/document-api/protocols/paidServiceProtocol)
- [Developer Portal](https://app.klingai.com/global/dev)Related Skills
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