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linkedin-post-researchLinkedIn 后期研究

Agent Skill

linkedin-post-research 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。

总安装

188

周安装

8

GitHub Stars

630

下载量

66
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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。

GitHub

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:linkedin-post-research(LinkedIn 后期研究)
来源仓库:https://github.com/gooseworks-ai/goose-skills
仓库路径:skills/linkedin-post-research
安装命令:
npx skills add https://github.com/gooseworks-ai/goose-skills --skill linkedin-post-research
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 linkedin-post-research

简介

该技能用于 LinkedIn 帖子内容的检索与分析。

  • 适合需要研究热门话题、行业观点或用户参与度模式。
  • 可根据关键词或时间范围筛选目标帖子集合。
  • 使用前应确认是否允许大规模内容抓取及平台政策合规性。
  • linkedin-post-research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

LinkedIn Post Research

Search LinkedIn for posts matching keywords via Apify. Returns posts sorted by engagement or date, with author info, full text, reaction counts, and direct URLs.

No LinkedIn cookies. No login. Just keywords in, posts out.

When to Auto-Load

Load this skill when:

  • User says "search LinkedIn posts", "what are people saying about X on LinkedIn", "find LinkedIn content about"
  • User wants to find high-engagement posts on a topic
  • User wants to identify who's posting about a specific topic (thought leader discovery)
  • User wants to find posts to extract commenters from (warm lead pipeline)

Prerequisites

Apify API Token

Required for searching LinkedIn posts. Set in .env:

APIFY_API_TOKEN=your_token_here

No LinkedIn cookies, login, or session tokens needed. That's the only setup.


How It Works

  1. Takes one or more keywords
  2. Calls the apimaestro/linkedin-posts-search-scraper-no-cookies Apify actor
  3. Returns posts with author, text, engagement metrics, date, and URL
  4. Deduplicates across keywords by activity_id
  5. Sorts by engagement (total reactions) descending, or by date

Quick Start

# Single keyword search
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI sourcing" --max-items 20

# Multiple keywords
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI sourcing" --keyword "recruiting automation" --max-items 30

# Sort by date (most recent first)
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --sort-by date_posted --max-items 20

# Output as CSV
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --output csv --output-file results.csv

# Summary table
python3 skills/capabilities/linkedin-post-research/scripts/search_posts.py \
  --keyword "AI agents" --output summary

CLI Reference

FlagDefaultDescription
--keyword, -k*required*Keyword to search (can be repeated for multiple keywords)
--max-items50Max posts to return per keyword
--sort-byrelevanceSort order: relevance or date_posted
--output, -ojsonOutput format: json, csv, summary
--output-filestdoutWrite output to file
--tokenenv varApify API token (overrides APIFY_API_TOKEN env var)
--timeout120Max seconds to wait for Apify run

Apify Actor Details

Actor: apimaestro/linkedin-posts-search-scraper-no-cookies

API call:

curl -X POST "https://api.apify.com/v2/acts/apimaestro~linkedin-posts-search-scraper-no-cookies/runs?token=$APIFY_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "keyword": "AI agents",
    "maxItems": 50,
    "sortBy": "date_posted"
  }'

Polling for results:

# Check run status
curl "https://api.apify.com/v2/acts/apimaestro~linkedin-posts-search-scraper-no-cookies/runs/{RUN_ID}?token=$APIFY_API_TOKEN"

# When status is SUCCEEDED, fetch results
curl "https://api.apify.com/v2/datasets/{DATASET_ID}/items?token=$APIFY_API_TOKEN"

Output Schema

{
  "author": "Jane Smith",
  "author_headline": "VP of Sales at Acme Corp",
  "author_profile_url": "https://www.linkedin.com/in/janesmith",
  "keyword": "AI sourcing",
  "reactions": 142,
  "comments": 28,
  "shares": 12,
  "reactions_by_type": {"LIKE": 100, "EMPATHY": 30, "PRAISE": 12},
  "date": "2026-04-01",
  "post_preview": "First 200 chars of the post text...",
  "full_text": "Complete post text...",
  "url": "https://www.linkedin.com/posts/...",
  "activity_id": "7447040447966826496",
  "hashtags": ["#AI", "#sales"],
  "is_repost": false,
  "content_type": "text"
}

Output Columns (CSV)

ColumnDescription
authorPost author name
author_headlineAuthor's LinkedIn headline
author_profile_urlAuthor's LinkedIn profile URL
keywordWhich search keyword matched
reactionsTotal reaction count
commentsComment count
sharesShare count
datePost date (YYYY-MM-DD)
post_previewFirst ~200 characters
urlDirect link to the LinkedIn post
activity_idUnique post identifier
hashtagsComma-separated hashtags

Cost

Apify charges per compute usage. ~50 posts costs approximately $0.01-0.05 depending on the actor's pricing tier. The script prints cost info after each run.

Error Handling

ErrorFix
APIFY_API_TOKEN not setAsk user to add it to .env
Apify run fails or times outRetry once. If still fails, try a broader keyword.
0 resultsKeyword may be too specific. Try broader terms.

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

按任务关键词查找相关 Skills

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

能力 4

展示第三方安全扫描或审计结果

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

Codex

33.68%
按下载量换算22

Claude

30.14%
按下载量换算20

Cursor

18.68%
按下载量换算12

Gemini CLI

10.29%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

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 warning/failed 结果,不能写成本站确认安全。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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