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Agent Skill · 研究检索

ads-linkedin(广告链接)

ads-linkedin 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。

ads-linkedin 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 14,067。

总安装 8,860周安装 383GitHub Stars 3,698下载 3,187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:ads-linkedin(广告链接)
来源仓库:https://github.com/agricidaniel/claude-ads
仓库路径:skills/ads-linkedin
安装命令:
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-linkedin
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/agricidaniel/claude-ads --skill ads-linkedin

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。

ads-linkedin 针对 LinkedIn Ads 执行深度审计,涵盖 27 项技术与管理指标评分。适用于 LinkedIn 广告账户的健康度评估,重点检查 Insight Tag 与 Conversions API。采用新术语体系(Campaigns 与 Ad Sets),需确认当前平台是否已同步更新。

要求 Insight Tag 正常上报且 CAPI 已启用,否则核心功能无法运行。输出带权重分值的健康报告,建议结合 benchmarks.md 理解 LinkedIn 特有基准值。

来源仓库内路径:skills/ads-linkedin

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/agricidaniel/claude-ads --skill ads-linkedin;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

ads-linkedin 怎么安装?

在终端执行 npx skills add https://github.com/agricidaniel/claude-ads --skill ads-linkedin。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

ads-linkedin 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。

ads-linkedin 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。

ads-linkedin 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。

ads-linkedin 用的人多吗?

公开数据是累计安装 8,860 次,近一周安装 383 次,下载 3,187 次,GitHub 3,698 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。

ads-linkedin 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,698 星,维护活跃度相对可查。

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
ads-linkedin

广告链接 · 本页

8,8603,698需要联网未明确通过

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

LinkedIn Ads Deep Analysis

Terminology note (Oct 2025): Campaign Groups are now called Campaigns, and Campaigns are now called Ad Sets. This skill uses the new terminology.

Process

  1. Collect LinkedIn Ads data (Campaign Manager export, Insight Tag status)
  2. Read ads/references/linkedin-audit.md for full 27-check audit
  3. Read ads/references/benchmarks.md for LinkedIn-specific benchmarks
  4. Read ads/references/scoring-system.md for weighted scoring
  5. Evaluate all applicable checks as PASS, WARNING, or FAIL
  6. Calculate LinkedIn Ads Health Score (0-100)
  7. Generate findings report with action plan

What to Analyze

Technical Setup (25% weight)

  • Insight Tag installed and firing on all pages (L01)
  • Conversions API (CAPI) active, launched 2025 (L02)
  • Conversion events configured for full funnel
  • Revenue attribution tracking enabled
  • Salesforce/HubSpot CRM integration (June 2025) enables closed-loop impression-to-revenue reporting

Audience Targeting (25% weight)

  • Job title targeting uses specific titles, not just functions (L03)
  • Company size filtering matches ICP (L04)
  • Seniority level appropriate for offer (L05)
  • Matched Audiences active: retargeting + contact lists (L06)
  • ABM company lists uploaded (up to 300,000 companies) (L07)
  • Audience expansion OFF for precision campaigns, ON for scale (L08)
  • Predictive audiences tested, replaced Lookalikes Feb 2024 (L09)

Creative Quality (20% weight)

  • Thought Leader Ads active, ≥30% budget allocation for B2B (L10)
  • Ad format diversity: ≥2 formats tested (L11)
  • Video ads tested (L12)
  • Creative refresh every 4-6 weeks (L13)

Lead Gen & Performance (15% weight)

  • Lead Gen Form ≤5 fields (13% CVR benchmark) (L14)
  • Lead Gen Form synced to CRM in real-time (L15)
  • Campaign objective matches funnel stage (L18)
  • A/B testing active: creative or audience (L19)
  • Message ad frequency ≤1 per 30-45 days (L20)

Bidding & Budget (15% weight)

  • Bid strategy: Start with Manual CPC. Maximum Delivery is the most expensive option. (L16)
  • Daily budget ≥$50 for Sponsored Content (L17)
  • CTR ≥0.44% for Sponsored Content (L21)
  • CPC within benchmark: $5-7 average, senior $6.40+ (L22)
  • Lead-to-opportunity rate tracked, not just CPL (L23)
  • Attribution: 30-day click / 7-day view configured (L24)
  • Demographics report reviewed monthly (L25)

Thought Leader Ads (TLA) Assessment

Thought Leader Ads use employee/executive personal posts as sponsored content. Non-employee members eligible since March 2025. 2-5x higher engagement than standard Sponsored Content.

  • CPC typically $2.29-$4.14 vs $13.23 for standard Sponsored Content
  • CTR typically 2-3x higher than corporate-branded ads
  • 2-5x higher engagement (includes non-employee member TLAs since March 2025)
  • Best for: B2B thought leadership, brand awareness, engagement

Evaluate:

  • Are TLAs being used? (If not, HIGH priority recommendation)
  • Are they getting ≥30% of total LinkedIn budget?
  • Are the right employees selected (industry credibility, active posters)?
  • Is post content authentic and valuable (not salesy)?

Ad Format Benchmarks

FormatKey Metric
Document Ads7.00% engagement rate
Conversation Ads50-60% open rate

Note: EU Sponsored Messaging (InMail/Conversation Ads) discontinued since Jan 2022.

LinkedIn Audience Network

Expert consensus is OFF. Quality is poor, and it dilutes campaign performance data. Disable LinkedIn Audience Network unless specifically testing with isolated budget.

ABM Strategy Assessment

For B2B Enterprise accounts:

  • Company list uploaded and segmented by tier (Tier 1, 2, 3)
  • Custom content per tier (personalized messaging)
  • Account penetration tracking (contacts reached per target account)
  • Integration with CRM/ABM platform (Demandbase, 6sense, etc.)

LinkedIn Context

SettingValue
Minimum audience size500 (for ads to run)
Lead Gen Form CVR benchmark13%
TLA CPC range$2.29-$4.14
Standard SC CPC$13.23 average
Hierarchy renameOct 2025 (Campaign Group → Campaign → Ad)
Predictive AudiencesReplaced Lookalikes Feb 2024

Key Thresholds

MetricPassWarningFail
CTR (Sponsored Content)≥0.44%0.30-0.44%<0.30%
CPC (average)≤$7.00$7-10>$10.00
Lead Gen CVR≥10%5-10%<5%
Message frequency≤1/30 days1/15-30 days>1/15 days
TLA budget share≥30%15-30%<15%

Output

LinkedIn Ads Health Score

LinkedIn Ads Health Score: XX/100 (Grade: X)

Technical Setup:   XX/100  ████████░░  (25%)
Audience:          XX/100  ██████████  (25%)
Creative:          XX/100  ███████░░░  (20%)
Lead Gen:          XX/100  █████░░░░░  (15%)
Budget & Bidding:  XX/100  ████████░░  (15%)

Deliverables

  • LINKEDIN-ADS-REPORT.md: Full 27-check findings with pass/warning/fail
  • TLA adoption roadmap (if not using)
  • ABM strategy recommendations (for B2B)
  • Lead Gen Form optimization priorities
  • Quick Wins sorted by impact

平台分布

Codex

36.56%
按下载量换算1,165

Claude

28.8%
按下载量换算918

Cursor

16.61%
按下载量换算529

Gemini CLI

9.34%
按下载量换算298

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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