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Scammer

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naxiaoduo
scammer

骗子.skill — 把骗局套路蒸馏成 AI,检测可疑消息,定位当前阶段,预判下一步。Distill scam patterns into AI, detect suspicious messages, locate current phase, predict next move.

Overview

Publishernaxiaoduo
RepositoryScammer.skill
Skill namescammer
Stars
81
Forks
12
Bundled files
16
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by naxiaoduo on GitHub. Read the source before you install it.

Installation

Install the Scammer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/naxiaoduo/Scammer.skill/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/naxiaoduo/Scammer.skill.git \
  .claude/skills/scammer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Scammer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Scammer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Scammer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Language / 语言: 根据用户第一条消息的语言,全程使用同一语言回复。 Detect the user's language from their first message and respond in the same language throughout.

骗子.skill(Claude Code 版)

触发条件

以下情况启动检测模式:

  • /detect-scam
  • /scammer [消息内容]
  • "帮我看看这条消息"
  • "这是诈骗吗"
  • "判断一下这个"
  • 用户直接粘贴一段可疑消息或截图

以下情况启动添加模式:

  • /add-scam
  • "我想添加一个骗局"
  • "记录一下这种骗法"
  • /update-scam {slug}

以下情况启动管理命令:

  • /list-scams:列出所有骗局库
  • /scam-stats:统计信息
  • /scam-rollback {slug} {version}:回滚版本
  • /scam-versions {slug}:列出历史存档
  • /delete-scam {slug}:删除本地骗局库(需用户明确确认)

工具使用规则

任务使用工具
读取截图/图片Read 工具(原生支持图片)
读取 PDF / TXT / MDRead 工具
写入/更新骗局库文件Write / Edit 工具
列出骗局库Bash → python3 ${CLAUDE_SKILL_DIR}/tools/pattern_writer.py --action list
版本管理(存档 / 递增 / 回滚 / 列表)Bash → python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py
删除骗局库(慎用)Bash → python3 ${CLAUDE_SKILL_DIR}/tools/pattern_writer.py --action delete --slug {slug} --force --base-dir ./scams

基础目录:骗局库写入 ./scams/{slug}/(相对于本项目目录)。


主流程 A:检测可疑消息

Step 1:接收输入

接受以下任意形式的输入:

  • 直接粘贴的文字消息
  • 截图(用 Read 工具读取图片内容)
  • 用户对话的描述("他说他是xxx,要我做xxx")
  • 多条消息的对话记录

如果用户没有提供消息,引导输入:

请提供可疑消息,可以:
  [A] 直接粘贴文字
  [B] 上传截图
  [C] 描述对方说了什么

Step 2:加载骗局库

用 Read 工具读取 ${CLAUDE_SKILL_DIR}/scams/ 目录下所有骗局的 tactic.md,以及用户本地添加的骗局库。

参考 ${CLAUDE_SKILL_DIR}/prompts/detection.md 中的匹配逻辑;若某骗局目录下有 Correction 记录,优先采纳其中的例外说明。

Step 3:分析输出

输出格式严格按照以下结构:

【{骗局类型}】第 {N} 阶段:{阶段名称}

├ 套路识别:{触发此判断的3个关键信号}
├ 已过阶段:{阶段1} → {阶段2} → {当前阶段}
├ 下一步预判:{骗子接下来大概率会说什么/做什么}
├ 心理钩子:{本阶段利用的心理弱点}
└ 建议:{具体行动建议,1-2句话}

置信度处理:

  • 高置信度(>85%):直接输出结论
  • 中置信度(60-85%):输出结论,附注"也可能是:{备选类型}"
  • 低置信度(<60%):列出2-3种可能,说明各自的判断依据
  • 无法判断:说明缺少什么信息,询问用户补充

无骗局判断:如确认不是诈骗,直接说"未检测到常见诈骗特征",说明原因,不要过度警惕。


主流程 B:添加新骗局样本

Step 1:基础信息录入(3个问题)

参考 ${CLAUDE_SKILL_DIR}/prompts/intake.md:

  1. 骗局类型名称(如:冒充公检法、杀猪盘)
  2. 核心特征(一句话:目标群体、主要套路、最终目的)
    • 示例:专门针对老年人,假冒医保局,诱导购买保健品
  3. 样本来源(亲身遭遇 / 朋友转发 / 新闻案例 / 反诈平台)

Step 2:原材料导入

样本怎么提供?

  [A] 直接粘贴聊天记录
  [B] 上传截图
  [C] 描述骗局流程
  [D] 提供案例链接或新闻报道

Step 3:提取套路

参考 ${CLAUDE_SKILL_DIR}/prompts/pattern_analyzer.md 提取:

线路 A(套路图谱):

  • 完整阶段划分(从接触到得手)
  • 每阶段的触发词/信号
  • 每阶段的目标和话术模板
  • 退出信号(目标不上钩时的转变)

线路 B(话术库):

  • 高频词汇和短语
  • 心理钩子类型(恐惧/贪婪/权威/情感/紧迫感/从众)
  • 信任建立手法
  • 常见伪装身份

Step 4:预览确认

向用户展示摘要(各5-8行),询问确认:

套路图谱摘要:
  - 骗局类型:{xxx}
  - 阶段数:{N} 个阶段
  - 核心套路:{xxx}
  ...

话术库摘要:
  - 核心心理钩子:{xxx}
  - 高频词汇:{xxx}
  ...

确认添加?还是需要调整?

Step 5:写入骗局库

用户确认后:

1. 创建目录(Bash):

bash
mkdir -p scams/{slug}/versions

2. 写入 tactic.md(Write 工具): 路径:scams/{slug}/tactic.md

参考 ${CLAUDE_SKILL_DIR}/prompts/tactic_builder.md 生成内容。

3. 写入 scripts.md(Write 工具): 路径:scams/{slug}/scripts.md

4. 写入 meta.json(Write 工具): 路径:scams/{slug}/meta.json

json
{
  "name": "{骗局名称}",
  "slug": "{slug}",
  "created_at": "{ISO时间}",
  "updated_at": "{ISO时间}",
  "version": "v1",
  "profile": {
    "target": "{目标群体}",
    "platform": "{主要平台}",
    "goal": "{最终目的}"
  },
  "tags": {
    "psychology": ["恐惧", "贪婪"],
    "method": ["冒充身份", "情感操控"]
  },
  "stages_count": {N},
  "sample_sources": ["..."],
  "corrections_count": 0
}

告知用户:

✅ 骗局样本已添加!

文件位置:scams/{slug}/
已加入检测库,下次 /detect-scam 时自动使用。

如果有新样本,随时 /add-scam 追加。

进化模式:追加样本

用户提供新样本时:

  1. 读取新内容
  2. Read 读取现有 scams/{slug}/tactic.md 和 scripts.md
  3. 参考 ${CLAUDE_SKILL_DIR}/prompts/merger.md 分析增量
  4. 存档当前快照(不改变 meta.json 中的版本号):
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action backup --slug {slug} --base-dir ./scams
  5. Edit 追加增量内容
  6. 更新 meta.json 中的 updated_at、stages_count 等字段(如有变化)
  7. 合并内容确认无误后,再递增版本号:
    bash
    python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action bump --slug {slug} --base-dir ./scams

进化模式:用户纠正

用户表达"判断错了"/"这不是诈骗"/"这是另一种骗法"时,按 ${CLAUDE_SKILL_DIR}/prompts/correction_handler.md 处理:

  1. 询问正确类型或正确判断
  2. 生成 correction 记录
  3. Edit 追加到对应文件的 ## Correction 记录 节
  4. 如果是全新骗局,引导进入添加模式

管理命令

/list-scams:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/pattern_writer.py --action list --base-dir ./scams

/scam-stats:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/pattern_writer.py --action stats --base-dir ./scams

/scam-rollback {slug} {version}:

bash
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action rollback --slug {slug} --version {version} --base-dir ./scams

/scam-versions {slug}(列出可回滚的快照目录名):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/version_manager.py --action list --slug {slug} --base-dir ./scams

/delete-scam {slug}(删除本地骗局目录,不可恢复;需用户明确确认后再执行):

bash
python3 ${CLAUDE_SKILL_DIR}/tools/pattern_writer.py --action delete --slug {slug} --force --base-dir ./scams

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Scammer AI skill do?

骗子.skill — 把骗局套路蒸馏成 AI,检测可疑消息,定位当前阶段,预判下一步。Distill scam patterns into AI, detect suspicious messages, locate current phase, predict next move.

Why use Scammer on TypingMind?

Because you install it once and use it with any model. Scammer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Scammer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/naxiaoduo/Scammer.skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Scammer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Scammer?

As many as you like. As long as a model supports skills, you can use Scammer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Scammer AI skill free?

Yes. It is published on GitHub by naxiaoduo under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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