Implement content policy compliance for Kling AI. Use when ensuring generated content meets guidelines or filtering inappropriate prompts. Trigger with phrases like 'klingai content policy', 'kling ai moderation', 'safe video generation', 'klingai content filter'.
npxskills add jeremylongshore/claude-code-plugins-plus-skills--skill klingai-content-policyLoading…
Kling AI enforces content policies server-side. Tasks with policy-violating prompts return task_status: "failed" with a content policy message. This skill covers pre-submission filtering to avoid wasted credits and API calls.
Kling AI prohibits prompts that generate:
| Category | Examples |
|---|---|
| Violence/gore | Graphic injuries, torture, weapons used violently |
| Adult/sexual | Explicit nudity, sexual acts, suggestive content |
| Hate/discrimination | Slurs, targeted harassment, supremacist imagery |
| Illegal activity | Drug manufacturing, terrorism, fraud instructions |
| Real people | Deepfakes of identifiable individuals without consent |
| Copyrighted characters | Trademarked characters (Mickey Mouse, Spider-Man) |
| Misinformation | Fake news, fabricated events presented as real |
| Self-harm | Suicide, eating disorders, self-injury instructions |
import re
class PromptFilter:
"""Filter prompts before sending to Kling AI to save credits."""
BLOCKED_PATTERNS = [
r"\b(nude|naked|explicit|nsfw|porn)\b",
r"\b(gore|dismember|torture|mutilat)\b",
r"\b(bomb|terroris|weapon|firearm)\b",
r"\b(suicide|self.harm|kill.yourself)\b",
r"\b(deepfake|impersonat)\b",
]
BLOCKED_TERMS = {
"blood splatter", "graphic violence", "child abuse",
"drug manufacturing", "hate speech",
}
def __init__(self):
self._patterns = [re.compile(p, re.IGNORECASE) for p in self.BLOCKED_PATTERNS]
def check(self, prompt: str) -> tuple[bool, str]:
"""Returns (is_safe, reason)."""
lower = prompt.lower()
for term in self.BLOCKED_TERMS:
if term in lower:
return False, f"Blocked term: '{term}'"
for pattern in self._patterns:
match = pattern.search(prompt)
if match:
return False, f"Blocked pattern: '{match.group()}'"
if len(prompt) > 2500:
return False, "Prompt exceeds 2500 character limit"
if len(prompt.strip()) < 5:
return False, "Prompt too short"
return True, "OK"
def sanitize(self, prompt: str) -> str:
"""Remove problematic terms and return cleaned prompt."""
for pattern in self._patterns:
prompt = pattern.sub("[removed]", prompt)
return prompt.strip()
Always include safety-related negative prompts:
DEFAULT_NEGATIVE_PROMPT = (
"violence, gore, blood, nudity, sexual content, "
"weapons, drugs, hate symbols, distorted faces, "
"watermark, text overlay, low quality, blurry"
)
def safe_request(prompt: str, negative_prompt: str = ""):
"""Build request with safety defaults."""
combined_negative = f"{DEFAULT_NEGATIVE_PROMPT}, {negative_prompt}".strip(", ")
return {
"model_name": "kling-v2-master",
"prompt": prompt,
"negative_prompt": combined_negative,
"duration": "5",
"mode": "standard",
}
class SafeKlingClient:
"""Kling client with pre-submission content filtering."""
def __init__(self, base_client):
self.client = base_client
self.filter = PromptFilter()
def text_to_video(self, prompt: str, **kwargs):
is_safe, reason = self.filter.check(prompt)
if not is_safe:
raise ValueError(f"Content policy violation: {reason}")
# Add safety negative prompt
kwargs.setdefault("negative_prompt", "")
kwargs["negative_prompt"] = (
f"{DEFAULT_NEGATIVE_PROMPT}, {kwargs['negative_prompt']}".strip(", ")
)
return self.client.text_to_video(prompt, **kwargs)
def handle_policy_rejection(task_id: str, result: dict):
"""Handle content policy rejections gracefully."""
status_msg = result["data"].get("task_status_msg", "")
if "content policy" in status_msg.lower() or "policy violation" in status_msg.lower():
return {
"error": "content_policy_violation",
"message": "Your prompt was rejected by Kling AI's content policy. "
"Please revise to remove restricted content.",
"task_id": task_id,
"credits_consumed": False, # policy rejections typically don't consume credits
}
return {"error": "generation_failed", "message": status_msg, "task_id": task_id}
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CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).