Klingai Common ErrorsSAFE
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
Overview
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
4f83675ca38aOBSERVED · 2026-10-09Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| claude-code | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: klingai-common-errors description: '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''. ' allowed-tools: Read, Write, Edit, Bash(npm:*), Grep version: 1.18.0 license: MIT author: Jeremy Longshore <[email protected]> tags: - saas - kling-ai - debugging - errors compatibility: Designed for Claude Code --- # 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 ``` ## Prerequisites - A sandbox workspace, synthetic or rights-cleared diagnostic brief, secret references, approved scope, redaction rules, draft-only destination, and incident owner. ## Instructions 1. Reproduce errors with sandbox fixtures only; do not log authorization headers, prompts, source assets, response bodies, or generated asset URLs. 2. Capture aggregate status, error class, credit use, policy/rights outcome, and task state while verifying redaction and retention contr
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__klingai-common-errors.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-09 | 4f83675ca38a | SAFE | B | 89 | first audit |
Questions
What does the Klingai Common Errors skill do?
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
Is Klingai Common Errors safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Klingai Common Errors access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Klingai Common Errors work with?
Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-09. The repository is watched, and a new audit runs when it changes — this is the first audit.