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social-media-agent社交媒体 Agent

Agent Skill

social-media-agent 用于查找、检索和筛选相关信息,适合在 Local Agent 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。

总安装

188

周安装

8

下载量

66
Local Agent

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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-agent(社交媒体 Agent)
来源仓库:https://skills.volces.com
仓库路径:social-media-agent
安装命令:
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。当前暂无明确安装命令,请以来源页面说明为准。

简介

social-media-agent 用于查找、检索和筛选相关信息,支持关键词匹配。

  • 适合在 Local Agent 中根据任务场景快速定位候选结果。
  • 可通过来源仓库和原始 README 继续核验具体用法。
  • 安装前需确认权限范围和维护状态,注意是否会触发联网或文件读写。
  • 建议结合安装命令验证实际能力边界和使用限制。

SKILL.md

Social Media Agent

Manage an X/Twitter account autonomously using only OpenClaw's built-in tools. No external APIs, no npm packages, no API keys needed.

Core Tools

  • browser — Post tweets, engage with posts, take screenshots
  • web_fetch — Scrape profiles, trending topics, news for content
  • sessions_spawn — Run content generation in parallel
  • cron — Schedule regular posting and engagement
  • memory_search / files — Track what was posted, engagement stats

Posting a Tweet

  1. Ensure Chrome is running with remote debugging OR use OpenClaw's built-in browser
  2. Navigate to x.com/compose/post
  3. Take a snapshot to find the text input
  4. Type the tweet text
  5. Click the Post button
  6. Verify with another snapshot
browser open → x.com/compose/post
browser snapshot → find textbox ref
browser act → click textbox ref
browser act → type tweet text
browser snapshot → find Post button ref
browser act → click Post button

Important timing: Wait 3-4 seconds after page loads before interacting.

Content Generation Strategy

Content Pillars

Rotate through these categories for balanced content:

Pillar%Examples
Industry Insights40%AI news commentary, tech analysis
Building in Public30%Progress updates, behind-the-scenes
Philosophy/Thought20%Hot takes, provocative questions
Engagement/Humor10%Memes, replies, community interaction

Content Pipeline

  1. Research: Use web_fetch on news sites (theverge.com, techcrunch.com, news.ycombinator.com)
  2. Generate: Spawn a content-agent via sessions_spawn with research results
  3. Store: Save drafts in memory/tweet-drafts-YYYY-MM-DD.json
  4. Review: Check drafts for quality, brand consistency
  5. Post: Use browser automation to publish
  6. Track: Log posted tweets in memory/social-log.json

Draft Format

{
  "text": "Tweet text under 280 chars",
  "topic": "What it's about",
  "hook": "Why it might engage"
}

Engagement Strategy

Posting Rules

  • Max 3-5 tweets per day — Quality over quantity
  • Min 45 seconds between actions — Avoid rate limiting
  • No spam — Genuine engagement only
  • Track everything — Log all posts and engagement

Growing Followers

  1. Post consistently (daily)
  2. Engage with relevant accounts (reply, quote tweet)
  3. Use trending topics when relevant
  4. Be authentic — no generic AI responses

Scheduling with Cron

Set up automated posting schedules:

Morning post: cron expr "0 9 * * *" — Industry insight
Afternoon post: cron expr "0 15 * * *" — Building update
Evening post: cron expr "0 21 * * *" — Hot take

Use sessionTarget: "isolated" with payload.kind: "agentTurn" for autonomous posting.

Anti-Patterns (Avoid)

  • Do NOT post more than 5 tweets per day (looks spammy)
  • Do NOT use generic engagement ("Great post!" "So true!")
  • Do NOT post without reading the content you're commenting on
  • Do NOT use API keys when browser automation works
  • Do NOT build external tools when OpenClaw native suffices

Analytics Tracking

Track engagement in memory/social-log.json:

{
  "date": "2026-02-08",
  "posted": 3,
  "platform": "x",
  "handle": "@YourHandle",
  "tweets": [
    {"text": "...", "time": "09:00", "topic": "ai-news"}
  ]
}

Review weekly: What topics got most engagement? Adjust strategy accordingly.

Quick Reference

For detailed content templates and examples, see references/content-templates.md.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

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能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Local Agent

74.36%
按下载量换算49

安全审计

暂无安全审计结果可展示。

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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