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Agent Skill · 研究检索

trending-ad-hook-spotter(趋势广告挂钩发现者)

trending-ad-hook-spotter 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。

trending-ad-hook-spotter 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,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 72,323。

总安装 188周安装 8GitHub Stars 630下载 66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:trending-ad-hook-spotter(趋势广告挂钩发现者)
来源仓库:https://github.com/gooseworks-ai/goose-skills
仓库路径:skills/trending-ad-hook-spotter
安装命令:
npx skills add https://github.com/gooseworks-ai/goose-skills --skill trending-ad-hook-spotter
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/gooseworks-ai/goose-skills --skill trending-ad-hook-spotter

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。

trending-ad-hook-spotter 用于查找、检索和筛选相关信息。适合根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令安装,需结合来源仓库和 README 核验用法。安装前建议确认权限范围、维护状态及是否会触发联网或文件读写。

当前介绍未说明是否分析广告文案效果,需进一步核实用途。

来源仓库内路径:skills/trending-ad-hook-spotter

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/gooseworks-ai/goose-skills --skill trending-ad…;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

    它需要接触敏感数据,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

trending-ad-hook-spotter 怎么安装?

在终端执行 npx skills add https://github.com/gooseworks-ai/goose-skills --skill trending-ad-hook-spot…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

trending-ad-hook-spotter 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。

trending-ad-hook-spotter 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

trending-ad-hook-spotter 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。

trending-ad-hook-spotter 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 次,GitHub 630 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。

trending-ad-hook-spotter 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
trending-ad-hook-spotter

趋势广告挂钩发现者 · 本页

188630接触敏感数据未明确未通过

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

Trending Ad Hook Spotter

Scan social platforms for what's trending in your space right now — viral posts, hot debates, breaking news, memes — and translate each trend into a concrete ad hook you can run while the topic is still hot.

Core principle: The highest-performing ads ride cultural and industry moments. This skill finds those moments before your competitors do and tells you exactly how to capitalize.

When to Use

  • "What's trending in our space that we could run ads about?"
  • "Find viral hooks for our paid campaigns"
  • "What topics are hot in [industry] right now?"
  • "I want to ride a trend with a paid campaign"
  • "What should we be running ads about this week?"

Prerequisites

  • Environment variable: APIFY_API_TOKEN — required for Reddit scraping (optional if using only web_search + HN API)
  • Web search access — your AI agent must support web_search or equivalent for Twitter/X and LinkedIn lookups
  • No API key needed for Hacker News (Algolia HN API is free and public)

Phase 0: Intake

  1. Your product — Name + one-line description
  2. Industry/category — What space are you in? (e.g., "AI sales tools", "developer infrastructure")
  3. ICP keywords — 5-10 keywords that define your buyer's world
  4. Competitor names — So we can spot when they become part of a trend
  5. Platforms to scan (default: all):

- Twitter/X - Reddit (specific subreddits if known) - LinkedIn - Hacker News

  1. Content velocity — How fast can you create ads? (Same-day / 2-3 days / Weekly)

Phase 1: Social Scanning

1A: Twitter/X Trend Scan (web_search)

Use web_search with site:x.com or site:twitter.com to find trending posts — no scraper or credentials needed:

# Industry trending topics
web_search: "<industry keyword> (viral OR trending OR hot take OR thread) site:x.com"

# Competitor mentions (momentum signals)
web_search: "<competitor1> OR <competitor2> (raised OR launched OR shut down OR acquired OR outage) site:x.com"

# Pain/frustration spikes
web_search: "<category> (broken OR frustrating OR tired of OR switched from) site:x.com"

Run 3-5 queries to cover:

  • Industry trending topics and hot takes
  • Competitor momentum signals (launches, outages, funding)
  • Pain/frustration spikes in the category
  • Viral threads with high engagement

Score each tweet/thread by engagement velocity (likes + retweets relative to account size and age).

1B: Reddit Trend Scan (Apify)

Use the trudax/reddit-scraper-lite actor to scan relevant subreddits for hot posts:

Browse specific subreddits (for trending/hot posts):

POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json

{
  "startUrls": [
    {"url": "https://www.reddit.com/r/SUBREDDIT1/hot/"},
    {"url": "https://www.reddit.com/r/SUBREDDIT2/hot/"}
  ],
  "maxItems": 30
}

Search by keyword (for specific topics):

POST https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs?token=$APIFY_API_TOKEN
Content-Type: application/json

{
  "searches": ["<industry keyword> OR <competitor>"],
  "maxItems": 30
}

Poll until the run finishes:

GET https://api.apify.com/v2/acts/trudax~reddit-scraper-lite/runs/{RUN_ID}?token=$APIFY_API_TOKEN

When status is SUCCEEDED, fetch results:

GET https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN

Output fields: Each item has dataType ("post" or "comment"), title (posts only), body, communityName, upVotes, numberOfComments (posts), url, createdAt.

Look for:

  • Posts with unusually high upvote/comment ratios
  • "What do you use for [X]?" threads (buying intent)
  • Complaint threads about incumbents
  • "I just switched from X to Y" posts

1C: LinkedIn Trend Scan (web_search)

Use web_search with site:linkedin.com/posts to find high-engagement KOL posts — no scraper or credentials needed:

web_search: "<industry keyword> site:linkedin.com/posts"
web_search: "<competitor_name> site:linkedin.com/posts"
web_search: "<KOL_name> <industry keyword> site:linkedin.com/posts"
web_search: "<trending topic> site:linkedin.com/pulse"

Run queries for:

  • 5-10 key opinion leaders (KOLs) in the space — search their names + topic keywords
  • Industry-level keyword searches to find viral posts
  • Competitor mentions from thought leaders

Identify high-engagement posts on topics relevant to your product category.

1D: Hacker News Scan (Algolia HN API)

Use the free Algolia HN Search API — no API key needed:

Search for relevant stories:

GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&hitsPerPage=20

Search for recent stories (past 7 days):

GET https://hn.algolia.com/api/v1/search?query=KEYWORD&tags=story&numericFilters=created_at_i>UNIX_TIMESTAMP_7_DAYS_AGO&hitsPerPage=20

Get front page stories (current trending):

GET https://hn.algolia.com/api/v1/search?tags=front_page&hitsPerPage=30

The response includes points, num_comments, title, url, and created_at for each story. Sort by points to find the highest-engagement discussions.

Run queries for:

  • Each ICP keyword
  • Each competitor name
  • The product category
  • Check front page for anything tangentially related

Phase 2: Trend Identification & Scoring

Trend Detection Framework

Group collected signals into trends. A "trend" is:

  • A topic appearing across 2+ platforms within the past 7 days
  • A single post/thread with exceptional engagement (10x+ the norm)
  • A breaking event (funding, acquisition, outage, launch) with cascading conversation

Score Each Trend

FactorWeightDescription
Recency25%How fresh? (< 24h = max, > 7 days = low)
Velocity25%Is engagement accelerating or decelerating?
Cross-platform20%Appearing on multiple platforms?
ICP relevance20%Does your target buyer care about this?
Product fit10%Can you credibly connect your product to this trend?

Total score out of 100. Urgency tiers:

  • 90-100: Run today — this peaks within 24-48h
  • 70-89: Run this week — 3-5 day window
  • 50-69: Worth testing — stable trend, less time pressure
  • Below 50: Monitor — not actionable yet

Phase 3: Hook Translation

For each trend scoring 50+, generate:

Ad Hook Formula

[Trend reference] + [Your unique angle] + [CTA tied to the moment]

Per Trend, Produce:

  1. Trend summary — What's happening in 2 sentences
  2. Why it's an ad opportunity — Connection to your product/ICP
  3. 3 hook variants:

- Newsjack hook — Reference the trend directly ("Everyone's talking about X. Here's what they're missing...") - Contrarian hook — Take the opposite stance ("Hot take: [trend] doesn't matter. Here's what does...") - Practical hook — Offer a solution related to the trend ("[Trend] means you need [your feature] now")

  1. Recommended format — Static / video / carousel / search ad
  2. Recommended platform — Where the trend is hottest
  3. Time window — How long before this trend fades

Phase 4: Output Format

# Trending Ad Hooks — [DATE]

Industry: [category]
Platforms scanned: [list]
Trends identified: [N]
Actionable hooks (score 50+): [N]

---

## Run Today (Score 90+)

### Trend: [Trend Title]
**What's happening:** [2-sentence summary]
**Engagement signal:** [X likes/comments across Y platforms in Z hours]
**Time window:** [Estimated hours/days before this fades]

**Hook 1 (Newsjack):** "[Ad headline]"
> [1-2 sentence body copy]
- Format: [Static/Video/Carousel]
- Platform: [Twitter/Meta/Google/LinkedIn]

**Hook 2 (Contrarian):** "[Ad headline]"
> [Body copy]

**Hook 3 (Practical):** "[Ad headline]"
> [Body copy]

---

## Run This Week (Score 70-89)

[Same format]

---

## Worth Testing (Score 50-69)

[Same format, briefer]

---

## Trend Velocity Dashboard

| Trend | Twitter | Reddit | LinkedIn | HN | Score | Window |
|-------|---------|--------|----------|----|----|--------|
| [Trend 1] | High | Medium | Low | — | 92 | 24h |
| [Trend 2] | Medium | — | High | Low | 78 | 5d |
| [Trend 3] | Low | Medium | — | Medium | 61 | 2w |

---

## Competitor Trend Involvement

| Trend | Competitor Riding It? | Their Angle | Your Counter-Angle |
|-------|----------------------|-------------|-------------------|
| [Trend] | [Y/N — who] | [Their take] | [Your differentiated take] |

Save to trending-hooks-[YYYY-MM-DD].md in the current working directory (or user-specified path).

Cost

ComponentCost
Twitter/X (web_search)Free
Reddit scraper (Apify)~$0.05-0.10
LinkedIn (web_search)Free
Hacker News (Algolia API)Free
Analysis & hook generationFree (LLM reasoning)
Total~$0.05-0.10 (or free if skipping Reddit Apify scraper)

Tools Required

  • Environment variable: APIFY_API_TOKEN — for Reddit scraping via Apify (optional — skill works without it using web_search fallback for Reddit)
  • Web search — built into your AI agent (for Twitter/X, LinkedIn)
  • Hacker News Algolia API — free, no key needed (https://hn.algolia.com/api/v1/)
  • No third-party libraries needed. All data collection uses HTTP APIs (requests or equivalent) and web_search.

Trigger Phrases

  • "What's trending we could run ads about?"
  • "Find viral hooks for our campaigns"
  • "What's hot in [space] this week?"
  • "Newsjacking opportunities for [client]"
  • "Run the trending hook spotter"

平台分布

Codex

33.48%
按下载量换算22

Claude

30.49%
按下载量换算20

Cursor

20.41%
按下载量换算13

Gemini CLI

9.58%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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