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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.zip

Installs 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。"
    }

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