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Agent Skill · 研究检索

newsletter-signal-scanner(时事通讯信号扫描仪)

newsletter-signal-scanner 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

newsletter-signal-scanner 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,674 个 Skill 里排第 68,654。

总安装 225周安装 9GitHub Stars 607下载 73核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:newsletter-signal-scanner(时事通讯信号扫描仪)
来源仓库:https://github.com/athina-ai/goose-skills
仓库路径:skills/newsletter-signal-scanner
安装命令:
npx skills add https://github.com/athina-ai/goose-skills --skill newsletter-signal-scanner
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/athina-ai/goose-skills --skill newsletter-signal-scanner

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

将订阅的新闻通讯转化为结构化情报流,提取竞争对手提及与市场趋势。支持按关键词活动分组监控,每周汇总一次高价值片段。帮助团队提前感知行业风向,优化内容规划与外展时机选择。需配置 AgentMail 账户与至少一个关键词活动才能启动扫描任务。

newsletter-signal-scanner 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/newsletter-signal-scanner

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/athina-ai/goose-skills --skill newsletter-sign…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

newsletter-signal-scanner 怎么安装?

在终端执行 npx skills add https://github.com/athina-ai/goose-skills --skill newsletter-signal-scanner。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

newsletter-signal-scanner 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

newsletter-signal-scanner 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

newsletter-signal-scanner 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

newsletter-signal-scanner 用的人多吗?

公开数据是累计安装 225 次,近一周安装 9 次,下载 73 次,GitHub 607 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

newsletter-signal-scanner 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
newsletter-signal-scanner

时事通讯信号扫描仪 · 本页

225607需要联网未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Newsletter Signal Scanner

Turn your newsletter subscriptions into a structured intelligence feed. Monitors an AgentMail inbox for incoming newsletters, extracts signal-relevant content by keyword campaign, and delivers a weekly digest of what matters — competitor mentions, ICP pain language, market shifts, and emerging topics.

When to Use

  • "Monitor industry newsletters for competitor mentions"
  • "Alert me when newsletters mention [topic] or [company]"
  • "What are newsletters writing about this week in our space?"
  • "Set up newsletter monitoring for [client]"

Phase 0: Intake

Newsletters to Monitor

  1. Which newsletters should be subscribed to and monitored? (List names or URLs)

- If unknown, ask: "What 3-5 newsletters does your ICP read?" — then use sponsored-newsletter-finder to discover others.

  1. Which AgentMail inbox should receive them? (Or should we create a new one?)

Keyword Campaigns

  1. Competitor names to track (e.g., "Clay", "Apollo", "Outreach")
  2. ICP pain-language terms to track (e.g., "outbound struggling", "pipeline dried up", "SDR ramp")
  3. Market shift terms (e.g., "AI SDR", "agent-led growth", "GTM engineer")
  4. Your brand name (to catch mentions)

Output

  1. Digest delivery: Slack channel, email, or markdown file? (default: markdown file)
  2. Frequency: daily or weekly? (default: weekly)

Save campaign config to clients/<client-name>/configs/newsletter-signals.json.

{
  "inbox_id": "<agentmail_inbox_id>",
  "keyword_campaigns": {
    "competitors": ["Clay", "Apollo", "Outreach", "Salesloft"],
    "pain_language": ["pipeline is down", "outbound isn't working", "SDR ramp"],
    "market_shifts": ["AI SDR", "GTM engineer", "agent-led"],
    "brand_mentions": ["YourCompany", "yourcompany.com"]
  },
  "newsletters": [
    {"name": "Exit Five", "from_domain": "exitfive.com"},
    {"name": "The GTM Newsletter", "from_domain": "gtmnewsletter.com"}
  ],
  "output": {
    "format": "markdown",
    "path": "clients/<client-name>/intelligence/newsletter-signals-[DATE].md"
  }
}

Phase 1: Scan Inbox

Use the agentmail capability to fetch new emails from the monitored inbox:

Fetch emails from inbox <inbox_id> since <last_scan_date>
Filter to: known newsletter senders (match against newsletters config)

For each email:

  • Extract subject, sender, date, full body text
  • Strip HTML → plain text for analysis

Phase 2: Apply Keyword Campaigns

For each newsletter email, scan for keyword matches:

for email in emails:
    matches = {}
    for campaign, keywords in keyword_campaigns.items():
        found = []
        for keyword in keywords:
            if keyword.lower() in email.body.lower():
                # Extract context: 50 chars before + keyword + 50 chars after
                context = extract_context(email.body, keyword)
                found.append({"keyword": keyword, "context": context})
        if found:
            matches[campaign] = found
    email.signal_matches = matches

Only include emails with at least one keyword match in the digest.

Phase 3: Extract Signal Snippets

For each matched email, extract clean signal snippets:

Competitor mention example:

Newsletter: The GTM Newsletter | Date: 2026-03-05 Campaign: competitors Keyword: "Clay" Context: "...teams that use Clay for enrichment are seeing 3x better personalization rates compared to..."

Pain language example:

Newsletter: Exit Five | Date: 2026-03-04 Campaign: pain_language Keyword: "outbound isn't working" Context: "...a lot of founders telling me outbound isn't working the way it used to. The reply rates I'm seeing..."

Phase 4: Output Format

# Newsletter Signal Digest — Week of [DATE]

## Summary
- Newsletters scanned: [N]
- Emails with signals: [N]
- Top trending topic: [topic]

---

## Competitor Mentions

### Clay
- **[Newsletter Name]** — [Date]
  > "[Context snippet]"
  Source: [email subject] | [URL if available]

### [Other Competitor]
...

---

## ICP Pain Language

Signals suggesting your ICP is feeling pain your product solves:

- **[Newsletter Name]** — [Date]
  > "[Context snippet]"
  — Relevance: [why this matters]

---

## Market Shift Signals

Emerging topics gaining newsletter coverage:

- **"[Topic]"** — mentioned in [N] newsletters this week
  > "[Context snippet]"

---

## Your Brand Mentions
[Any mentions of your company or product]

---

## Recommended Actions
1. [Specific action based on signals — e.g., "Exit Five is covering AI SDR fatigue — good moment to publish our take"]
2. [Competitive response if needed]

Save to clients/<client-name>/intelligence/newsletter-signals-[YYYY-MM-DD].md.

Phase 5: Setup — Subscribe to Newsletters

For first-time setup, subscribe the AgentMail address to target newsletters:

  1. Get the AgentMail inbox address (via agentmail capability)
  2. For each newsletter, visit subscription page and submit the AgentMail address
  3. Confirm subscriptions (check inbox for confirmation emails)
  4. Allow 1-2 weeks of accumulation before first full digest

Scheduling

Run weekly (Monday morning recommended):

# Every Monday at 7am — before the team's standup
0 7 * * 1 python3 run_skill.py newsletter-signal-scanner --client <client-name>

Cost

ComponentCost
AgentMail inboxDepends on AgentMail pricing
Email parsing + keyword matchingFree (local logic)
TotalNear-zero ongoing cost

Tools Required

  • AgentMail API — for inbox access
  • Upstream skill: agentmail capability

Trigger Phrases

  • "Scan newsletters for this week's signals"
  • "What are industry newsletters saying about [topic]?"
  • "Run newsletter signal scanner for [client]"
  • "Set up newsletter monitoring"

平台分布

Claude

33.58%
按下载量换算25

Codex

32.66%
按下载量换算24

Cursor

18.46%
按下载量换算13

Gemini CLI

9.27%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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