CO
compliance_review
内容安全与合规审核工具。在生成任何视觉内容前,必须确保不触碰平台红线。
Install
mkdir -p .claude/skills/compliance-review && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16317" && unzip -o skill.zip -d .claude/skills/compliance-review && rm skill.zipInstalls to .claude/skills/compliance-review
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.
内容安全与合规审核工具。在生成任何视觉内容前,必须确保不触碰平台红线。35 charsno explicit “when” trigger
About this skill
平台合规审查
你不仅是导演,也是发行制片。必须过滤:
极度血腥暴露
- 将"斩首"弱化为"致命一击"
- 将"血肉模糊"弱化为"激烈战斗"
- 过度血腥暴露的描写都需要弱化
政治违禁品敏感隐喻
- 政治、违禁品等敏感隐喻必须过滤
- 敏感内容都需要进行适当处理
NSFW 关键词库
["血肉模糊", "斩首", "断肢", "色情", "裸露", "血腥", "残忍", "恐怖", "虐杀"
def execute(params):
import sqlite3
import os
content = params.get("text_content", "")
shot_id = params.get("shot_id", "")
# 实际项目中,这里通常会调用阿里云/腾讯云的内容安全 API (Text Moderation)
# 这里做简单的本地敏感词拦截作为示例
nsfw_keywords = ["血肉模糊", "斩首", "断肢", "色情", "裸露", "血腥", "残忍", "恐怖", "虐杀"]
found_keywords = []
for word in nsfw_keywords:
if word in content:
found_keywords.append(word)
if found_keywords:
return {
"status": "blocked",
"feedback": f"触发合规风控:包含敏感描写:{', '.join(found_keywords)}。请修改表达方式(如使用剪影或隐晦镜头替代)。"
}
# 如果有 shot_id,更新 shot 的状态
if shot_id:
# 数据库路径
db_path = os.path.join(os.path.dirname(__file__), "../../project/evolution_log.db")
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
cursor.execute('UPDATE shots SET status = ? WHERE shot_id = ?', ('compliance_passed', shot_id))
conn.commit()
conn.close()
return {
"status": "safe",
"message": "内容安全风控通过。"
}