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Agent Skill · 开发

social-media-analytics(社交媒体分析)

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。

social-media-analytics 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 4,842。

总安装 7,440周安装 310GitHub Stars 公开资料未说明下载 2,480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
MIT-0
版本
1.0.1

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:social-media-analytics(社交媒体分析)
来源仓库:https://github.com/snoopyrain/social-media-analytics
安装命令:
openclaw skills install social-media-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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install social-media-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。

聚合全平台数据生成表现分析与指标计算报告。适用于日常复盘与KPI达成度评估场景。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。输入查询语句后返回对应维度的数据切片与趋势图。样本数据不可直接等同总体事实,需说明统计口径边界。

social-media-analytics 属于开发类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install social-media-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

social-media-analytics 怎么安装?

在终端执行 openclaw skills install social-media-analytics。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

social-media-analytics 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

social-media-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。

social-media-analytics 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

social-media-analytics 用的人多吗?

公开数据是累计安装 7,440 次,近一周安装 310 次,下载 2,480 次。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。

social-media-analytics 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
social-media-analytics

社交媒体分析 · 本页

7,440—接触敏感数据MIT-0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

name
social-media-analytics
description
Track social media performance and analytics across all platforms. Use when the user says 'show my analytics', 'check social media performance', 'how are my posts doing', 'engagement report', 'post metrics', 'view stats', or wants to see performance data for Facebook, Instagram, Threads, YouTube, or TikTok accounts.
version
1.0.0
metadata
openclaw
emoji
📊
homepage
https://boring-doc.aiagent-me.com/getting-started/mcp.html
requires
config

Boring Social Analytics

Track performance and engagement across all your social media platforms. Powered by Boring.

Security & Data Handling

  • MCP link is a credential: Your MCP Server URL (https://boring.aiagent-me.com/mcp/t/xxxxx...) contains an embedded authentication token. Treat it like a password — do not share it publicly.
  • Token scope: The embedded token is read-only for analytics. It can only fetch performance metrics and account metadata. It cannot publish, delete, or modify any content on your social media accounts.
  • Token storage: The token is stored server-side in Boring's database (MongoDB on DigitalOcean). It is never written to your local filesystem. You can regenerate or revoke it anytime at boring.aiagent-me.com/settings.
  • Data flow: Analytics queries are sent from Boring's server (Google Cloud, us-central1) to the platform's API on your behalf. Only performance metrics are retrieved — no content is uploaded or modified.
  • No local credentials: No local API keys, environment variables, or secrets are needed. All auth is embedded in the MCP link.
  • Third-party service: This skill relies on Boring, an open-source social media management tool. Source code: github.com/snoopyrain.

Prerequisites

  1. Sign up at boring.aiagent-me.com with Google
  2. Connect accounts — supports Facebook, Instagram, Threads, YouTube, TikTok
  3. Get your MCP link: Go to Settings → copy your MCP Server URL (contains your auth token — treat it like a password)
  4. Add to Claude: Paste the MCP link as a Connector — no install, no API key needed

Available Analytics Tools

ToolData SourceBest For
boring_get_performanceReal-time platform APIAccount-level overview (reach, engagement, followers)
boring_get_video_analyticsReal-time platform APIPer-post/video metrics (views, likes, comments, shares)
boring_get_posts_performanceDaily snapshots (collected at 2 AM)Historical post performance over date ranges
boring_get_publish_historyBoring databasePublishing history and status tracking

Workflow

Step 1: List Accounts

Call boring_list_accounts to see all connected platforms. Show a summary to the user.

Step 2: Determine What the User Wants

User RequestTool to Use
"How is my account doing?"boring_get_performance
"Show my best posts"boring_get_video_analytics
"Performance over the last month"boring_get_posts_performance
"What did I post recently?"boring_get_publish_history
"Compare platforms"boring_get_performance for each platform

Step 3: Fetch Data

Account-Level Performance
boring_get_performance(
  account_id="<account_id>",
  platform="instagram",
  period="week"       // "day", "week", or "month"
)

Returns metrics like reach, follower count, engagement rate, profile views.

Per-Post Analytics (Real-Time)
boring_get_video_analytics(
  account_id="<account_id>",
  platform="instagram",
  limit=20             // max 100
)

Returns per-post data: views, likes, comments, shares for up to 100 recent posts.

Historical Post Performance (Snapshots)
boring_get_posts_performance(
  account_id="<account_id>",
  since="2025-12-01",  // YYYY-MM-DD (default: 30 days ago)
  until="2025-12-31",  // YYYY-MM-DD (default: today)
  limit=20             // max 100
)

Returns post-level engagement, metrics, and content from daily collected snapshots.

Publishing History
boring_get_publish_history(
  limit=20,
  platform="facebook"  // optional filter
)

Returns recent publishing activity with status and post IDs.

Step 4: Present Results

Format the data clearly for the user:

For account overview: Show key metrics in a summary table For post analytics: Rank posts by engagement, highlight top performers For cross-platform comparison: Side-by-side metrics across platforms For historical data: Show trends over time

Metrics by Platform

Facebook

  • page_media_view: Total video views
  • page_post_engagements: Likes, comments, shares
  • page_total_actions: Total page actions

Instagram

  • reach: Accounts reached
  • follower_count: Total followers
  • profile_views: Profile visits
  • total_interactions: Likes + comments + saves + shares
  • Reels: ig_reels_avg_watch_time, ig_reels_video_view_total_time

Threads

  • views: Post views
  • likes, replies, reposts, quotes
  • followers_count: Account followers

YouTube

  • views, likes, comments, shares
  • estimatedMinutesWatched: Total watch time
  • averageViewDuration: Average view duration
  • subscribersGained / subscribersLost

TikTok

  • Video views, likes, comments, shares
  • Account-level performance metrics

Cross-Platform Comparison

When the user asks to compare platforms, fetch boring_get_performance for each connected account and present a unified table:

| Platform   | Reach   | Engagement | Followers |
|-----------|---------|------------|-----------|
| Facebook  | 12,500  | 1,200      | 5,000     |
| Instagram | 8,300   | 2,100      | 3,200     |
| Threads   | 3,100   | 450        | 1,800     |
| YouTube   | 15,000  | 3,500      | 2,100     |

Error Handling

ErrorSolution
InvalidApiKeyMCP link may be invalid — regenerate it at boring.aiagent-me.com Settings
InvalidAccountIdRun boring_list_accounts to get valid IDs
TokenExpiredReconnect account at boring.aiagent-me.com
No data returnedAccount may be newly connected — data collection runs daily at 2 AM

Documentation

Full API docs: boring-doc.aiagent-me.com

平台分布

OpenClaw

88.99%
按下载量换算2,207

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。目前只有一个公开来源,建议同时核对源仓库。

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