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Skill Ugc Discovery

OrganizationPopular
ZJU-REAL
skill-ugc-discovery

发现用户生成内容(UGC)。搜索与创作者品牌/账号相关的粉丝内容、测评、提及和社区讨论, 输出高价值 UGC 列表与互动建议。当用户说"谁提到了我"、"粉丝内容"、"品牌提及"、 "UGC 发现"、"用户口碑"、"测评搜索"、"社区讨论"时触发。

Overview

PublisherZJU-REAL
RepositoryEasel
Skill nameskill-ugc-discovery
Stars
3.5K
Forks
535
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

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

  • Open source

    Published by ZJU-REAL on GitHub. Read the source before you install it.

Installation

Install the Skill Ugc Discovery 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/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-ugc-discovery
  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/ZJU-REAL/Easel.git /tmp/Easel
mkdir -p .claude/skills
cp -r /tmp/Easel/skills/openclaw/skill-ugc-discovery .claude/skills/skill-ugc-discovery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill Ugc Discovery 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 Skill Ugc Discovery 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 Skill Ugc Discovery 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.

UGC 内容发现

搜索与创作者品牌/账号相关的用户生成内容,发现粉丝内容、测评、提及和社区讨论,输出可互动的 UGC 列表。

输入

字段必填说明
brand_keywords是品牌名/账号名,可多个(逗号分隔)
platforms否聚焦平台(小红书/B站/微博/知乎/抖音),默认全平台
content_type否reviews / mentions / fan_art / complaints / all(默认 all)
time_range否recent / this_month / this_quarter(默认 recent)

输出

markdown
# UGC 内容发现报告

## 发现概览
- 搜索关键词: {keywords}
- 搜索平台: {platforms}
- 发现 UGC 内容: {count} 条
- 正面/中性/负面: {positive}/{neutral}/{negative}

## 高价值 UGC(推荐互动/转发)
| # | 平台 | 内容摘要 | 来源链接 | 互动量估计 | 情感 | 建议动作 |
|---|------|---------|---------|-----------|------|---------|

## 负面反馈(需关注)
| # | 平台 | 内容摘要 | 来源链接 | 严重程度 | 建议回应 |
|---|------|---------|---------|---------|---------|

## 互动建议
- {具体建议: 转发/评论/联动/感谢}

三条发现路径

路径 1 — 平台搜索(主路径)

用 WebSearch 搜索创作者/品牌名相关内容:

搜索关键词组合:

  • "{账号名} 推荐" / "{账号名} 测评" / "{品牌名} 体验"
  • "{账号名} site:xiaohongshu.com" / "site:bilibili.com"
  • "{账号名} 好物" / "{账号名} 同款"

按 platforms 参数聚焦平台,未指定时逐平台搜索。

路径 2 — 话题/标签监控

搜索创作者品牌话题和关联标签:

  • "#{账号名}# site:weibo.com" — 微博话题
  • "#{品牌话题}#" — 跨平台品牌话题
  • "{账号名} 话题" / "{品牌名} 标签"

路径 3 — 社区讨论扫描

搜索论坛、问答社区、讨论帖:

  • "{品牌名} 怎么样" / "{产品名} 好用吗" — 知乎/贴吧
  • "{品牌名} 值得买吗" / "{账号名} 靠谱吗" — 购买决策讨论
  • "{品牌名} 吐槽" / "{品牌名} 避坑" — 负面反馈定向搜索

执行步骤

  1. 确认关键词:从用户输入获取 brand_keywords。若有 Profile,从 identity.md 补充账号名、品牌名、产品名等关键词。
  2. 确定搜索范围:根据 platforms 参数确定目标平台;根据 content_type 调整搜索关键词侧重(reviews 侧重"测评/推荐",complaints 侧重"吐槽/避坑")。
  3. 执行三条路径:
    • 路径 1:对每个平台执行 2-3 组关键词搜索(WebSearch)
    • 路径 2:搜索品牌话题和标签
    • 路径 3:搜索社区讨论
  4. 内容采集:对搜索结果中高相关的链接,用 WebFetch 获取内容摘要和互动数据。
  5. 去重与分类:去除重复结果,按情感倾向分类(正面/中性/负面)。
  6. 情感判断:基于内容文本判断情感倾向,区分事实性提及和评价性内容。
  7. 价值排序:按互动量和内容质量排序,筛选出高价值 UGC(值得互动/转发的内容)。
  8. 负面标注:单独列出负面反馈,按严重程度排序,给出建议回应策略。
  9. 互动建议:针对高价值 UGC 给出具体互动建议(转发并感谢 / 评论区互动 / 联动合作邀约)。
  10. 输出报告:按输出模板生成完整报告,保存到 outputs/。

Profile 感知

有 Profile 时:

  • 读取 identity.md 获取账号名、品牌名、产品线关键词,自动扩展搜索关键词
  • 读取 platforms.md 确定活跃平台,优先搜索这些平台
  • 读取 audience.md 判断哪些 UGC 来自目标受众群体(更具互动价值)
  • 读取 style.md 匹配互动建议的语气和方式

无 Profile 时:

  • 用户必须提供 brand_keywords,否则提示用户补充
  • 全平台搜索,不做平台优先级排序
  • 互动建议给出通用策略
  • 附注"提供 Profile 可获得更精准的 UGC 发现和互动建议"

规则

  1. 区分事实与分析 — 搜索到的内容是事实,情感判断是分析,两者分开标注
  2. 必须附来源链接 — 每条发现的 UGC 必须附上来源 URL
  3. 不编造 UGC — 搜索无结果时如实报告"未发现相关 UGC",不捏造内容
  4. 优先可操作内容 — 排序时优先展示高互动量、值得回应的 UGC
  5. 负面内容不回避 — 负面反馈单独列出,给出建设性的回应建议
  6. 标注数据局限 — WebSearch 结果有时效和覆盖限制,明确标注搜索范围和局限性

自研溯源与参考项目见同目录 EASEL-META.md。

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 Skill Ugc Discovery AI skill do?

发现用户生成内容(UGC)。搜索与创作者品牌/账号相关的粉丝内容、测评、提及和社区讨论, 输出高价值 UGC 列表与互动建议。当用户说"谁提到了我"、"粉丝内容"、"品牌提及"、 "UGC 发现"、"用户口碑"、"测评搜索"、"社区讨论"时触发。

Why use Skill Ugc Discovery on TypingMind?

Because you install it once and use it with any model. Skill Ugc Discovery 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 Skill Ugc Discovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ZJU-REAL/Easel/tree/main/skills/openclaw/skill-ugc-discovery. 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 Skill Ugc Discovery?

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 Skill Ugc Discovery?

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

Is the Skill Ugc Discovery AI skill free?

Yes. It is published on GitHub by ZJU-REAL under the Apache-2.0 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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