Industry Intelligence Radar logo

Industry Intelligence Radar

CommunityPopular
chubbyguan
industry-intelligence-radar

行业情报雷达:多源扫描(X/即刻/V2EX/HN) → 关键词过滤 → 趋势检测 → 每日情报简报。触发词:行业情报、竞品监控、热点扫描、情报雷达

Overview

Publisherchubbyguan
Repositorychubbyskills
Skill nameindustry-intelligence-radar
Stars
1.2K
Forks
147
Bundled files
1
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.

  • 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 chubbyguan on GitHub. Read the source before you install it.

Installation

Install the Industry Intelligence Radar 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/chubbyguan/chubbyskills/tree/main/industry-intelligence-radar
  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/chubbyguan/chubbyskills.git /tmp/chubbyskills
mkdir -p .claude/skills
cp -r /tmp/chubbyskills/industry-intelligence-radar .claude/skills/industry-intelligence-radar
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Industry Intelligence Radar 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 Industry Intelligence Radar 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 Industry Intelligence Radar 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.

行业情报雷达

核心价值

信息差优势:早知道 = 早行动 = 早收益

数据源

数据源接入方式是否需配置信号强度
Hacker Newsscan.py 内置(Algolia API)否(免费)⭐⭐⭐⭐
V2EXscan.py 内置(官方热门 API)否(免费)⭐⭐⭐
36kr / 虎嗅 / 少数派等scan.py RSS 源(config.rss)否(填 RSS 地址即可)⭐⭐⭐
X/TwitterAgent 联网搜索 / X API需 X API Key⭐⭐⭐⭐⭐
即刻Agent 联网搜索需搜索能力⭐⭐⭐⭐

scan.py 仅用 Python 标准库即可跑通 HN + V2EX + 任意 RSS 源,零依赖、无需 API Key。 X/即刻没有稳定的公开接口,由 Agent 用联网搜索能力补充(见 Phase 1)。

关键词矩阵

用户兴趣领域

yaml
AI/Agent:
  - "AI agent" OR "AI 工具" OR "LLM" OR "大模型"
  - "Claude" OR "GPT" OR "Gemini" OR "DeepSeek"
  - "MCP" OR "tool use" OR "function calling"

半导体:
  - "半导体" OR "芯片" OR "chip" OR "semiconductor"
  - "台积电" OR "TSMC" OR "英伟达" OR "NVIDIA"

航天:
  - "航天" OR "火箭" OR "卫星" OR "SpaceX"
  - "星链" OR "Starlink"

新能源:
  - "新能源" OR "电动车" OR "电池"
  - "特斯拉" OR "Tesla" OR "比亚迪"

游戏:
  - "游戏" OR "Steam" OR "Switch" OR "PS5"
  - "米哈游" OR "原神" OR "黑神话"

跨境电商:
  - "跨境电商" OR "TikTok Shop" OR "SHEIN"
  - "独立站" OR "DTC"

创业/投资:
  - "创业" OR "融资" OR "投资"
  - "YC" OR "a16z" OR "红杉"

工作流程

Phase 1: 多源扫描

① 脚本扫描(HN + V2EX + RSS,免费、可 cron)

bash
# 用内置关键词矩阵扫最近 24 小时,输出简报到文件
python3 scripts/scan.py --hours 24 --output 简报-$(date +%F).md

# 自定义关键词 / 追加 RSS 源(36kr、虎嗅、少数派等)
python3 scripts/scan.py --config keywords.json --hours 24

keywords.json 示例:

json
{
  "keywords": {
    "AI/Agent": ["AI agent", "LLM", "Claude", "MCP"],
    "半导体": ["半导体", "NVIDIA", "TSMC"]
  },
  "high_signal": ["融资", "发布", "launch", "raise"],
  "rss": ["https://www.36kr.com/feed", "https://sspai.com/feed"]
}

② Agent 联网补充(X / 即刻,需搜索能力)

脚本覆盖不到的实时社交信号,由 Agent 用联网搜索补充,再并入简报:

搜索 X/Twitter:"AI agent OR LLM OR 大模型" 最近 24 小时高互动内容
搜索即刻:"AI OR Agent OR 创业" 高质量讨论

Phase 2: 信号过滤

过滤规则:

  1. 去重:同一事件只保留最高质量来源
  2. 时效:只保留 24 小时内的内容
  3. 信号强度:
    • 🔴 高信号:融资、发布、政策变化、重大合作
    • 🟡 中信号:产品更新、行业讨论、观点碰撞
    • 🟢 低信号:日常动态、重复信息

Phase 3: 趋势检测

检测维度:

  1. 突发趋势:某话题突然大量出现
  2. 持续趋势:某话题持续一周以上高频出现
  3. 新兴趋势:新概念/新工具首次出现

Phase 4: 生成情报简报

输出格式:

markdown
# 📡 行业情报简报 - YYYY-MM-DD

## 🔴 高信号(必须关注)

### 1. [事件标题]
- **来源**:X/Twitter @xxx
- **时间**:2 小时前
- **摘要**:一句话概括
- **影响**:对我/行业的影响
- **行动建议**:是否需要立即响应

## 🟡 中信号(值得了解)

### 2. [事件标题]
- **来源**:即刻 @xxx
- **摘要**:一句话概括
- **关联**:与我关注的 XX 领域相关

## 📈 趋势观察

### [趋势名称]
- **热度**:⬆️ 上升 / ⬇️ 下降 / ➡️ 平稳
- **持续时间**:X 天
- **相关讨论**:[链接1] [链接2]

## 💡 机会洞察

基于今日情报,发现以下潜在机会:
1. [机会1]
2. [机会2]

## 📊 数据统计

- 扫描源:5 个
- 原始条目:150+
- 筛选后:25 条
- 高信号:3 条

Cron 配置

yaml
# 每日早报(工作日 8:30)
schedule: "30 8 * * 1-5"
deliver: feishu

# 可选:午间快报(12:00)
schedule: "0 12 * * 1-5"
deliver: feishu

输出目标

  1. 飞书群:每日情报推送
  2. 知识库:高价值情报存入 wiki/📡 外部输入/情报/
  3. 选题库:发现好选题自动进入选题池

反模式

  • ❌ 不要追求全量,信号 > 数量
  • ❌ 不要只翻译,要有自己的判断
  • ❌ 不要忽略中文社区(即刻、V2EX)
  • ✅ 每条情报必须有「对我有什么用」的结论
  • ✅ 优先独家/一手信息源

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 Industry Intelligence Radar AI skill do?

行业情报雷达:多源扫描(X/即刻/V2EX/HN) → 关键词过滤 → 趋势检测 → 每日情报简报。触发词:行业情报、竞品监控、热点扫描、情报雷达

Why use Industry Intelligence Radar on TypingMind?

Because you install it once and use it with any model. Industry Intelligence Radar 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 Industry Intelligence Radar in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/chubbyguan/chubbyskills/tree/main/industry-intelligence-radar. 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 Industry Intelligence Radar?

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 Industry Intelligence Radar?

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

Is the Industry Intelligence Radar AI skill free?

Yes. It is published on GitHub by chubbyguan 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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