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Agent Skill · 开发

linkedin-analytics(链接分析)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

linkedin-analytics 是开发类 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,按安装量在开发类的 21,746 个 Skill 里排第 14,075。

总安装 759周安装 31GitHub Stars 23下载 243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:linkedin-analytics(链接分析)
来源仓库:https://github.com/publora/skills
仓库路径:skills/linkedin-analytics
安装命令:
npx skills add https://github.com/publora/skills --skill linkedin-analytics
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/publora/skills --skill linkedin-analytics

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

linkedin-analytics 用于辅助数据清洗、汇总和统计口径生成。适合处理 CSV/Excel 文件、发现异常值或准备图表数据。需确认数据来源和时间范围,避免将样本当作全量事实。涉及敏感数据导出时应先确认脱敏方式和权限边界。

linkedin-analytics 属于开发类 Skill,可作为该场景下的辅助能力补充。建议保留原始字段含义,并在分析结果中标注计算逻辑。

来源仓库内路径:skills/linkedin-analytics

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/publora/skills --skill linkedin-analytics;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

linkedin-analytics 怎么安装?

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

linkedin-analytics 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。

linkedin-analytics 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。

linkedin-analytics 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。

linkedin-analytics 用的人多吗?

公开数据是累计安装 759 次,近一周安装 31 次,下载 243 次,GitHub 23 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。

linkedin-analytics 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
linkedin-analytics

链接分析 · 本页

75923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

LinkedIn Analytics

Get detailed analytics for your LinkedIn posts and profile using the Publora MCP server. Track impressions, engagement, follower growth, and interact with posts through reactions and comments.

Prerequisites

Plans: Starter (free), Pro, Premium - LinkedIn is available on all plans including free.

Getting Started

  1. Create account at publora.com/register (free)
  2. Connect LinkedIn via OAuth in Publora Dashboard
  3. Get API key at publora.com/settings/api
  4. Configure MCP in Claude Desktop (~/.claude/claude_desktop_config.json):
{
  "mcpServers": {
    "publora": {
      "type": "http",
      "url": "https://mcp.publora.com",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

REST API Fallback

If the MCP server is unavailable or returns errors, use the REST API directly:

Base URL: https://api.publora.com/api/v1

Authentication: Use x-publora-key header (NOT Authorization: Bearer):

# Get your connected platforms
curl -X GET "https://api.publora.com/api/v1/platform-connections" \
  -H "x-publora-key: sk_your_api_key"

# Get post statistics
curl -X POST "https://api.publora.com/api/v1/linkedin-post-statistics" \
  -H "x-publora-key: sk_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "platformId": "linkedin-abc123",
    "postedId": "urn:li:share:7123456789012345678",
    "queryTypes": "ALL"
  }'

# Get account statistics
curl -X POST "https://api.publora.com/api/v1/linkedin-account-statistics" \
  -H "x-publora-key: sk_your_api_key" \
  -H "Content-Type: application/json" \
  -d '{
    "platformId": "linkedin-abc123",
    "queryTypes": "ALL"
  }'

Platform ID Format: linkedin-{id} where {id} is from /platform-connections response.

Example IDs: linkedin-Tz9W5i6ZYG, linkedin-abc123xyz

📖 Full API documentation: docs.publora.com

Analytics Tools

linkedin_post_stats

Get engagement metrics for a specific LinkedIn post.

Parameters:

  • postedId: LinkedIn post URN (e.g., urn:li:share:123456 or urn:li:ugcPost:123456)
  • platformId: Platform connection ID (e.g., linkedin-abc123)
  • queryTypes (optional): Metrics to fetch: IMPRESSION, MEMBERS_REACHED, RESHARE, REACTION, COMMENT

Response includes:

  • Impressions (total views)
  • Unique impressions (members reached)
  • Reactions count
  • Comments count
  • Shares/reposts
  • Engagement rate

linkedin_account_stats

Get aggregated statistics for your LinkedIn account.

Parameters:

  • platformId: Platform connection ID
  • queryTypes (optional): Metrics to fetch
  • aggregation (optional): DAILY or TOTAL (default: TOTAL)

linkedin_followers

Get follower count or growth over time.

Parameters:

  • platformId: Platform connection ID
  • period (optional): lifetime or daily
  • dateRange (optional): For daily period: {start: {year, month, day}, end: {year, month, day}}

linkedin_profile_summary

Get a combined profile overview with followers and stats.

Parameters:

  • platformId: Platform connection ID
  • dateRange (optional): Date range for stats

Engagement Tools

linkedin_create_reaction

React to a LinkedIn post.

Parameters:

  • postedId: LinkedIn post URN
  • platformId: Platform connection ID
  • reactionType: One of the following:
TypeDescription
LIKEStandard thumbs up
PRAISEClapping hands / applause
EMPATHYHeart / love
INTERESTLightbulb / insightful
APPRECIATIONSupportive
ENTERTAINMENTFunny / laughing

linkedin_delete_reaction

Remove your reaction from a post.

Parameters:

  • postedId: LinkedIn post URN
  • platformId: Platform connection ID

linkedin_create_comment

Post a comment on a LinkedIn post (max 1,250 characters).

Parameters:

  • postedId: LinkedIn post URN
  • platformId: Platform connection ID
  • message: Comment text (max 1,250 characters)
  • parentComment (optional): Comment URN for nested replies

linkedin_delete_comment

Remove a comment you made.

Parameters:

  • postedId: LinkedIn post URN
  • commentId: Comment URN or numeric ID
  • platformId: Platform connection ID

Example Prompts

Weekly Performance Review

Analyze my LinkedIn performance for the last 7 days.
Show me:
1. Which posts performed best
2. My engagement rate trends
3. Follower growth
4. Recommendations for improvement

Post Analysis

Get detailed stats for my last 5 LinkedIn posts and identify patterns in what content resonates with my audience.

Engagement Campaign

React with PRAISE to my colleague's post about their promotion (urn:li:share:123456) and add a congratulatory comment.

Follower Tracking

Show my LinkedIn follower growth for the last 30 days. How many new followers did I gain each week?

Metrics Reference

MetricDescription
IMPRESSIONTotal times content appeared in feeds
MEMBERS_REACHEDUnique LinkedIn members who saw the post
RESHARENumber of reposts/shares
REACTIONTotal reactions (all types combined)
COMMENTNumber of comments

Engagement Rate Benchmarks

Average LinkedIn engagement rates by follower count:

FollowersGood Engagement Rate
< 5K3-5%
5K-50K2-3%
50K+1-2%

Good performing posts typically have:

  • 2x your average impressions
  • Comment-to-reaction ratio above 10%
  • Engagement rate above your baseline

Important Notes

  1. Analytics delay: LinkedIn analytics may take up to 24 hours to fully populate. Querying immediately after posting returns partial data.
  2. URN formats: LinkedIn URLs use urn:li:activity:xxx but the API requires urn:li:share:xxx or urn:li:ugcPost:xxx. Use the postedId from Publora's get_post response for accurate URNs.
  3. Caching: Analytics responses may be cached. The response includes a cached field indicating if data came from cache.
  4. Rate limits: LinkedIn has approximately 200+ API calls per hour. Implement backoff on 429 errors.

Troubleshooting

ErrorCauseSolution
"Platform ID not found"Invalid connection IDRun list_connections to get valid IDs
"Post not found"Wrong URN formatUse urn:li:share: or urn:li:ugcPost: format
429 Too Many RequestsRate limitedWait and retry with exponential backoff
"message cannot exceed 1250 characters"Comment too longShorten comment to under 1,250 chars

平台分布

Codex

35.03%
按下载量换算85

Claude

34.12%
按下载量换算83

Cursor

18.53%
按下载量换算45

Gemini CLI

10.17%
按下载量换算25

安全审计

Gen Agent Trust Hub

通过

Socket

通过

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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